Location: Toronto; Canada; Vancouver; Ottawa; Montreal
Workplace: Hybrid
WHO ARE WE?
Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems.
We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that.
We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft.
We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us!
ABOUT NORTH:
North https://cohere.com/north is Cohere's cutting-edge AI workspace platform, designed to revolutionize the way enterprises utilize AI. It offers a secure and customizable environment, allowing companies to deploy AI while maintaining control over sensitive data. North integrates seamlessly with existing workflows, providing a trusted platform that connects AI agents with workplace tools and applications.
WHY THIS ROLE?
This role offers a unique opportunity to shape how enterprises harness the power of AI in real-world applications. As a bridge between our core North product and our clients’ engineering teams, you’ll be at the forefront of solving complex problems and securely integrating AI into critical sectors such as finance, healthcare, and telecommunications. Our esteemed clients include industry leaders like RBC, Dell, and LG CNS.
We are seeking engineers who deeply care about customers and want to work at the cutting edge of Agentic AI.
In this role, you will:
- Lead end-to-end deployment of North in private cloud and on-premises environments, including planning, configuration, testing, and rollout.
- Partner with enterprise IT teams to assess infrastructure, security requirements, and data management practices.
- Experiment at a high velocity and with a high level of quality to engage our customers and ultimately deliver solutions that exceed their expectations
- Design and implement deployment strategies tailored to client needs, ensuring compliance with data privacy and security standards.
- Troubleshoot and resolve deployment-related technical issues, providing timely solutions to minimize downtime.
You may be a good fit if:
- You have experience with and enjoy working directly with customers
- You have experience deploying enterprise software in private/hybrid cloud environments
- You have proven experience administering production Kubernetes clusters and expertise with Helm
- Familiarity with DevOps practices, CI/CD pipelines, and tools like Git for version control
- You have strong expertise in cloud infrastructure (Azure, AWS, GCP), networking, and virtualization
- You excel in fast-paced environments and can execute while priorities and objectives are a moving target
FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS:
- A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch.
- Full health and dental benefits, including a separate budget for mental health.
- RRSP matching, 401K, Pension Scheme.
- 100% Parental Leave top-up for up to 6 months, for either parent.
- Annual enrichment benefits:
Arts & culture, fitness/wellness, quality time, and a workspace improvement credit.
Education & learning stipend for conferences, courses, and coaching.
- 6 weeks of paid vacation (30 working days!)
- Budget for traveling to other offices if you are remote, plus an annual company offsite.
HOW AND WHERE WE WORK:
- Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon.
- For those in the office: a daily lunch program, plenty of snacks, and regular community and social events.
- For those not near an office: a co-working benefit so you can work alongside others in your city.
- Everyone receives a $500 home office stipend to set up your workspace properly.
If any of the above doesn’t line up exactly with your experience, we still encourage you to apply.
We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs.
We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider.
Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers https://cohere.com/careers page.
ГибридToronto; Canada; Vancouver; Ottawa; Montreal; We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities
Location: United States
Senior Engineering Manager, Data & AI
Lead the engineering team behind Foundry, Insights, Intel, and Voice: the agents, analytics, and data intelligence of the modern freight platform.
About the Role
Remote, United States. Some travel is required for team onsites, customer visits, and industry events. Relocation assistance is not provided.
The Senior Engineering Manager, Data & AI leads the engineering group behind Foundry, Insights, Intel, and Voice. You'll own the group's technical strategy, delivery, and quality, hire and develop its engineers, and stay hands-on by prototyping, writing evals, reading traces, and reviewing architecture in depth.
The team is about eight engineers today and growing. It also owns the shared foundation those products run on: a context graph that connects loads, trips, carriers, drivers, customers, documents, and conversations; event-sourced platform data streaming into the warehouse; and the evals, tracing, guardrails, and model routing every agent depends on.
Alvys facilitates more than $1 billion in funds every month across invoices, carrier payments, and driver settlements. Behind that volume is one of the richest operational datasets in freight. This team turns it into agents that do real work and intelligence customers can't get anywhere else.
Engineering leaders at Alvys are builders. Expect to spend about a third of your time building. You'll set the standard for how an AI-first team works: coding agents in the daily workflow, evals before scale, and production evidence over demos.
The platform runs on .NET (C#, and increasingly F#), TypeScript, and Python on Azure and AKS, with Cosmos DB, Postgres, Elasticsearch, Snowflake, dbt, and Fivetran underneath.
We're looking for someone who treats AI as a first-class material, both in what we build for customers and in how the engineering team works.
Industry Insight
Freight runs on phone calls, emails, PDFs, and tribal knowledge. The U.S. trucking industry is worth approximately $1 trillion today and is projected to grow by roughly 60% to nearly $1.5 trillion over the next decade.
Yet the work that moves that freight is still largely manual. Nearly 580,000 active U.S. motor carriers operate in a highly fragmented market; 91.5% run 10 or fewer trucks, and 99.3% run 100 or fewer. Few of these businesses will ever build a data team of their own. Every check call answered, rate confirmation read, and exception caught by software is time back for a small team running on thin margins.
Freight data is also structurally messy. A single load spans brokers, carriers, drivers, shippers, and documents, each with its own identifiers, and the truth lives across EDI messages, phone calls, and free text. Generic AI tooling doesn't model any of this. That's why we're building a context graph grounded in how freight actually moves.
Agents can now answer the phone, read documents, query operational data, and take actions inside a TMS. In freight, those actions move trucks and money. They must be correct, auditable, and safe.
About Alvys
Alvys is building the operating system for modern freight. Our AI-powered, cloud-native platform brings dispatch, driver mobile, safety and compliance, billing and settlements, native EDI, reporting, integrations, and automation into one product.
We were founded in 2020 by freight industry insiders who were tired of software built by people who had never moved a load. That combination of deep customer empathy and ambitious technology still defines us. We visit customers, learn how the work actually happens, prototype quickly, debate ideas openly, and turn the best ones into products people rely on.
More than 3,000 trucking and brokerage companies use Alvys today, including larger fleets with increasingly sophisticated operations. We've raised $77M to date, including a $40M Series B. That gives us real momentum and room to make bold bets, while remaining early enough that a great engineering leader can materially shape the product, team, and company.
We are building more than a modern interface for a traditional TMS. Foundry, our agent platform within Alvys, helps freight teams make decisions and complete work, and this team builds it. You'll work with curious, direct, low-ego people who solve hard problems, move quickly from prototype to production, and measure customer impact.
Our Principles
AI makes building cheap. It does not make judgment cheap.
The constraint has moved from writing code to deciding what to build and proving it is right. Agents belong in the middle of the pipeline. People remain accountable at both ends. These principles turn that into how we work every day.
Own the outcome
You own what you ship. "AI wrote it" is not an answer.
Judgment stays human. People decide what matters and whether the result is correct.
Verify independently
Generation and verification are separate. Tests, review, and approval run independently of the agent that did the work.
Autonomy is earned per workflow. Agents advance only on measured precision against human-verified outcomes. No number, no promotion.
Design for control
AI-first means security-first. Customer data stays on approved infrastructure under managed identity.
Cost is an engineering constraint. Every shared workflow has termination conditions and bounded fan-out.
Build durable systems
Knowledge is tool-agnostic. Reviewed intent lives once; vendor-specific machinery is generated from it.
Multiple vendors are a design assumption. Durable workflows don't couple to one model or harness.
Twice is a pattern. Automate repeated work and share it within 48 hours.
The Data & AI Portfolio
The Data & AI portfolio covers Foundry, our embedded automation and agent platform, including a unified agent chat that answers questions and takes actions; Insights, conversational analytics grounded in each customer's own operating data; Intel, proprietary data intelligence drawn from third-party, licensed, and proprietary data sources; and Voice, AI voice and chat agents for load status, driver check calls, and the follow-ups in between. It also includes the shared foundation: the context graph, the data platform that feeds it, and the evals, tracing, guardrails, and model routing behind every agent.
Why This Role
Few engineering leadership roles combine frontier AI work, a proprietary dataset, and an industry this underserved. This one does.
You build at the frontier, in production.
Context graphs, self-learning agents, voice agents, and agentic automation are still being figured out across the industry. Here you ship them to real customers, on live freight operations, not benchmarks.
You work with data no one else has.
More than 3,000 trucking and brokerage companies run on Alvys, and more than $1 billion in funds moves through the platform every month. Combined with third-party and licensed sources, that data is the raw material for intelligence no single fleet or brokerage could build alone.
Your work changes how an industry operates.
With 91.5% of carriers running 10 or fewer trucks, most of our customers will never hire a data team. The agents you build give a small business the leverage of a much larger one.
You own a portfolio, not a feature.
Four products share one platform. You set its architecture, choose its models and vendors, and decide where the team invests as it grows.
You shape the team from the start.
The group is about eight engineers today. You'll hire the next wave and set the standard for how an AI-first engineering team works at Alvys.
You stay close to the decisions.
You report to the Head of Engineering, work directly with customers and our Forward Deployed Engineering team, and have a direct line into company planning, backed by a $40M Series B.
What You'll Be Responsible For
Leading and Growing the Team
Manage, coach, and develop a team of about eight engineers, including senior engineers and tech leads, and grow it as the portfolio expands.
Hire senior and staff engineers, and keep the quality bar high as the team scales.
Run the team AI-first, with coding agents in the daily workflow and clear standards for how AI-written code is reviewed, tested, and shipped.
Owning Technical Strategy
Set technical direction for agents, data, and the context graph, and make the build, buy, and model calls with cost, quality, and speed in view.
Make tradeoffs across four products that share one platform, including what gets built, what gets cut, and where the team invests.
Building Agents That Learn
Own the agent development lifecycle from prototype to production to continuous improvement.
Build self-learning loops so agents improve from outcomes, user corrections, and transcripts, and make that improvement measurable.
Make evals a release gate. No agent ships without tests for quality, safety, latency, and cost.
Data and the Context Graph
Own the context graph that links loads, trips, carriers, drivers, customers, documents, and conversations, and the entity resolution that keeps it trustworthy.
Partner on the data platform that feeds it, including event streams, CDC into Snowflake, data quality, and lineage, so agents and analytics share one source of truth.
Capture decision traces (the inputs gathered, the rule applied, any exception, who approved it, and why) so precedent becomes searchable for agents and people, while rules stay explicit.
Combine third-party, licensed, and proprietary data sources into intelligence customers can act on, with the provenance, licensing terms, and tenant boundaries of each source respected.
Safety, Isolation, and Reliability
Design agents that change data with scoped permissions, human approvals, and audit trails, and defend against prompt injection and tool misuse.
Enforce tenant isolation and least privilege across every agent, tool, and data path.
Own reliability and unit economics. Track cost per task, per call, and per tenant, and keep margins healthy as usage grows.
Staying Hands-On
Spend about a third of your time building: prototype, write evals, read traces, and debug production.
Review your team's designs and code with real depth, and stay current on models and tools, separating what works in production from what demos well.
Cross-Functional Partnership
Work as a peer to product and design leadership on direction, architecture, sequencing, and delivery.
Work directly with customers and our Forward Deployed Engineering team, and turn repeated patterns into platform features.
The AI Fluency We Expect
We measure AI fluency by how you verify, not by how much you use AI. More autonomy is not always better. You match the level of autonomy to the risk of the work, and you hold yourself and the team to the same five competencies.
Delegation:
You decide whether to use AI at all, which task to hand off, and how much autonomy it gets.
Description:
You state goals, requirements, and limits clearly, from a single prompt up to project instructions, specs, and policy.
Discernment:
You check output against evidence: diffs, acceptance checks, evals, and production monitoring.
Diligence:
You own the effects, including data access, permissions, memory isolation, budgets, and kill switches.
Systems:
You know how models, context, tools, harnesses, and memory work, and where each one fails.
How You Work With Agents
Design multi-agent systems on paper before you build them. For each step, choose a rule, a small model, a frontier model, or a person, and measure cost per outcome, not cost per token.
Start from code-orchestrated workflows and add model-led autonomy only where the task needs exploration. Keep agent-to-agent handoffs few, and give each agent a contract: inputs, allowed tools, and output schema.
Put limits in code, not in prompts: hooks, sandboxed worktrees, and a stop condition, retry cap, and budget on every loop.
Separate the agent that writes from the agent that checks, and give the checker fresh context.
Work in an explore, plan, execute, verify, and compound rhythm, where every correction becomes a rule, skill, hook, or test.
Move fluently across Claude Code, Codex, and Cursor, and choose an editor-first or agent-first surface based on who should hold the controls for the next step.
Where You Take the Team
Bring every engineer to running goal-based loops, where specs and checks are written first, never weakened to pass, and run by the agent itself.
Move the team from steering every turn to designing the system that steers the agent: its context, its harness, and its loop.
Build toward agents that run continuously in hosted sandboxes, each with its own least-privilege identity, a named owner, a budget, and a tested kill switch, with risk-scaled human review on financial actions, auth, settlements, and customer data.
Close the improvement loop. Capture traces, run error analysis on real failures every week, encode the fixes, and gate every change to rules, memory, or evals behind evals and a human approver. Self-improving never means self-approving.
Minimum Qualifications
8+ years building software, including 3+ years managing engineers.
You've grown senior engineers and tech leads and remain a hands-on builder who can prototype, debug production, and review code credibly.
Production LLM systems.
You've shipped LLM-powered products to real users, not demos, and can explain what broke, what you measured, and what you changed.
Agentic engineering in your own work.
You build with coding agents every day and can show the multi-agent workflows, contracts, hooks, and loops you put into production, and the checks that kept them honest.
Depth in agent systems.
You've built with tool use, function calling, MCP, orchestration, memory, and retrieval, and you understand where agents fail.
Evaluation discipline.
You've built eval systems that combine offline suites, online metrics, human review, and transcript analysis, and used them to gate releases.
Strong data engineering judgment.
You've worked with event streams, CDC, cloud warehouses, dbt, and data quality, and you know how the shape of the data limits what models can do.
Distributed systems in production.
You've designed and operated production services with real reliability requirements.
Multi-tenant security.
You've secured multi-tenant SaaS and isolated customer data, and you treat agent permissions as a security boundary.
Language fluency.
You write Python or TypeScript fluently and are comfortable reading C#, F#, and .NET. Experience with F# or another functional language is a plus.
Startup-stage fit.
You've operated at Series B/C velocity amid ambiguity, thin support, competing priorities, and a bias toward shipping and learning.
Clear technical communication.
You can explain a tradeoff to an engineer, a customer, and an executive.
Preferred Qualifications
Knowledge graphs, context graphs, entity resolution, or GraphRAG in production.
Real-time voice agents, including telephony, speech-to-text, text-to-speech, turn-taking, and latency budgets.
Fine-tuning, reinforcement learning from feedback, or prompt optimization against eval sets.
Embedded automation or workflow platforms such as Activepieces, n8n, or Temporal.
SRE experience, or a record of running systems other teams depend on.
Logistics or freight experience, or another vertical where data is deeply entangled with operations.
Founder or early-stage engineering leadership experience.
A history of hiring, growing, and retaining excellent engineers.
Built by people who've moved freight. Come build the intelligence layer with us.
Learn more at
alvys.com
Location: Remote
Workplace: Remote
WHY HARVEY
At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come.
This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched.
Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you.
At Harvey, the future of professional services is being written today — and we’re just getting started.
ROLE OVERVIEW
We're hiring a Sr. Infrastructure Engineer to own the shared layer that every Harvey IT system runs on. You'll join Core IT Engineering & Infrastructure, reporting to Dave Vega, Director of IT, alongside engineers who own identity and collaboration, Microsoft platforms, networking, and client platforms.
Harvey is cloud-first. We run no servers or data centers of our own. Our IT infrastructure is cloud tenants, SaaS configuration, office networks across a growing global footprint, and the automation that ties them together. Today that cross-cutting work is done on the side by each platform owner. This role makes it someone's primary job, so it gets built once, done well, and doesn't break quietly.
WHAT YOU'LL DO
You'll own the shared infrastructure, automation and reliability work that cuts across every IT platform.
- IT cloud accounts and tenants. Own access, guardrails and cost for the cloud accounts IT runs (AWS, Azure, GCP projects for IT tooling). Be the BizTech engineering partner to Security and Infrastructure on tenant-level changes, such as cloud migrations that touch Entra and M365.
- Infrastructure as code for IT. Build and run the Git repos, CI pipelines and review process for IT configuration (Okta, Jamf, Intune, Google Workspace). Platform owners keep owning their config. You own the framework they all use.
- IT automation and provisioning. Own the automation behind identity lifecycle and IT workflows: SCIM and provisioning flows, onboarding and offboarding orchestration across systems, and IT workflows in Serval.
- Monitoring, backup and resilience. Set up health checks and alerting for critical IT systems and integrations, config drift detection, SaaS backup (Google, Slack, M365) and tested recovery runbooks.
- Scripts and internal tooling. Take over the scripts and admin utilities that live on individual laptops today. Put them in source control, document them and keep them running.
- Office site standard. Work with Network and AV/Media teams to define the repeatable technical template for new offices: configuration, monitoring and documentation each site copies. Network and AV build execution stays with their owners.
- Engineering practices. Raise the bar on change control, documentation and runbooks across the pillar, so primaries and backups can cover for each other.
- Certificates, domains and DNS. Track and renew every certificate IT depends on (Apple Push, SAML signing, SSL, Wi-Fi/802.1X). Work with Network and CorpSec teams to own and manage DNS NS solutions for IT. Build expiry monitoring to avoid surprises.
WHAT YOU HAVE
- 6+ years in corporate IT engineering, systems engineering or SRE, with at least 2 years owning shared infrastructure or automation for a SaaS-first company.
- Strong infrastructure-as-code experience. You've managed real systems with Terraform or similar, in Git, with pull-request review and CI.
- Solid scripting in Python plus one of Bash, PowerShell or Go. You write code other people can read and maintain.
- Hands-on with identity and provisioning: SAML, OIDC, SCIM and lifecycle automation in Okta or Entra.
- Working knowledge of at least one major cloud (AWS, Azure or GCP): IAM, accounts and cost basics.
- Comfort with DNS, TLS and certificate management, and basic enterprise networking.
- You've built monitoring and alerting that people actually trust, and written runbooks that someone else used successfully.
- Clear written communication. You can explain a change, its risk and its rollback to non-engineers.
BONUS POINTS
- Terraform providers for Okta, Google Workspace or Jamf, or config-as-code tools for Intune
- Serval or similar IT automation platforms
- SaaS backup and recovery tools for Google Workspace, Slack or M365
- Multi-site office rollouts across regions, including working with local vendors and ISPs
- Experience at a fast-growing company where company headcount grew faster than the IT team
COMPENSATION
$153,000 - $210,500 USD
DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES HERE https://harveyai.notion.site/Harvey-Candidate-Privacy-Notices-319ac3fcdd7a803bb807d5094f249922?pvs=74.
#LI-RB1
Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.
We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai
Location: New York
Workplace: Hybrid
WHY HARVEY
At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come.
This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched.
Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you.
At Harvey, the future of professional services is being written today — and we’re just getting started.
ROLE OVERVIEW
We're hiring a Sr. Infrastructure Engineer to own the shared layer that every Harvey IT system runs on. You'll join Core IT Engineering & Infrastructure, reporting to Dave Vega, Director of IT, alongside engineers who own identity and collaboration, Microsoft platforms, networking, and client platforms.
Harvey is cloud-first. We run no servers or data centers of our own. Our IT infrastructure is cloud tenants, SaaS configuration, office networks across a growing global footprint, and the automation that ties them together. Today that cross-cutting work is done on the side by each platform owner. This role makes it someone's primary job, so it gets built once, done well, and doesn't break quietly.
WHAT YOU'LL DO
You'll own the shared infrastructure, automation and reliability work that cuts across every IT platform.
- IT cloud accounts and tenants. Own access, guardrails and cost for the cloud accounts IT runs (AWS, Azure, GCP projects for IT tooling). Be the BizTech engineering partner to Security and Infrastructure on tenant-level changes, such as cloud migrations that touch Entra and M365.
- Infrastructure as code for IT. Build and run the Git repos, CI pipelines and review process for IT configuration (Okta, Jamf, Intune, Google Workspace). Platform owners keep owning their config. You own the framework they all use.
- IT automation and provisioning. Own the automation behind identity lifecycle and IT workflows: SCIM and provisioning flows, onboarding and offboarding orchestration across systems, and IT workflows in Serval.
- Monitoring, backup and resilience. Set up health checks and alerting for critical IT systems and integrations, config drift detection, SaaS backup (Google, Slack, M365) and tested recovery runbooks.
- Scripts and internal tooling. Take over the scripts and admin utilities that live on individual laptops today. Put them in source control, document them and keep them running.
- Office site standard. Work with Network and AV/Media teams to define the repeatable technical template for new offices: configuration, monitoring and documentation each site copies. Network and AV build execution stays with their owners.
- Engineering practices. Raise the bar on change control, documentation and runbooks across the pillar, so primaries and backups can cover for each other.
- Certificates, domains and DNS. Track and renew every certificate IT depends on (Apple Push, SAML signing, SSL, Wi-Fi/802.1X). Work with Network and CorpSec teams to own and manage DNS NS solutions for IT. Build expiry monitoring to avoid surprises.
WHAT YOU HAVE
- 6+ years in corporate IT engineering, systems engineering or SRE, with at least 2 years owning shared infrastructure or automation for a SaaS-first company.
- Strong infrastructure-as-code experience. You've managed real systems with Terraform or similar, in Git, with pull-request review and CI.
- Solid scripting in Python plus one of Bash, PowerShell or Go. You write code other people can read and maintain.
- Hands-on with identity and provisioning: SAML, OIDC, SCIM and lifecycle automation in Okta or Entra.
- Working knowledge of at least one major cloud (AWS, Azure or GCP): IAM, accounts and cost basics.
- Comfort with DNS, TLS and certificate management, and basic enterprise networking.
- You've built monitoring and alerting that people actually trust, and written runbooks that someone else used successfully.
- Clear written communication. You can explain a change, its risk and its rollback to non-engineers.
BONUS POINTS
- Terraform providers for Okta, Google Workspace or Jamf, or config-as-code tools for Intune
- Serval or similar IT automation platforms
- SaaS backup and recovery tools for Google Workspace, Slack or M365
- Multi-site office rollouts across regions, including working with local vendors and ISPs
- Experience at a fast-growing company where company headcount grew faster than the IT team
COMPENSATION
$153,000 - $210,500 USD
DEPENDING ON YOUR LOCATION, AN APPLICANT PRIVACY NOTICE MAY APPLY TO YOU. YOU CAN FIND ALL OF OUR APPLICANT PRIVACY NOTICES HERE https://harveyai.notion.site/Harvey-Candidate-Privacy-Notices-319ac3fcdd7a803bb807d5094f249922?pvs=74.
#LI-RB1
Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.
We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai
Location: Remote (Canada)
Workplace: Remote
BUILD SOMETHING PEOPLE LOVE
Wealthsimple is Canada’s leading financial innovator. The company offers a full suite of simple, sophisticated financial products across managed investing, do-it-yourself trading, cryptocurrency, tax filing, spending and saving. Wealthsimple currently serves more than 4 million Canadians and holds over $169 billion in assets under administration. The company was founded in 2014 by a team of financial experts and technology entrepreneurs, and is headquartered in Toronto, Canada.
We're proud of what we've built — and we're just getting started. Read our Culture Manual https://www.wealthsimple.com/en-ca/culture and learn more about how we work https://www.wealthsimple.com/en-ca/careers.
ABOUT THE ROLE
We are looking for a curious, hands-on security professional early in their career to join our Detection & Response team as an Incident Response Developer. You’ll report to the Manager of Detection & Response and work closely with senior responders to investigate security incidents, improve our response processes and build automation that helps us scale. You’ll get hands-on experience with real incidents and the mentorship to grow into the craft.
The ideal candidate has a foundation in security fundamentals, some hands-on exposure to investigations or security operations, and real enthusiasm for automating repetitive work. You’re a problem-solver who stays calm when things get busy, asks good questions and wants to learn from experienced teammates.
WHAT YOU'LL DO
- Strengthen our incident response capabilities by building relationships with Engineering teams, writing new playbooks and automating manual steps.
- Own investigations from start to finish: triage, evidence collection, analysis, containment and documentation.
- Act as Incident Commander for low- and medium-severity incidents, and support senior responders on high-severity ones.
- Turn recurring incident types into repeatable workflows (intake, playbook, automation, closure), from the first design through to the tooling behind them.
- Report incident trends and metrics that inform team priorities.
- Work with our Security Engineers to monitor, refine and expand our SIEM and SOAR platforms.
- Work with the HR, Fraud and Privacy teams on investigations into potentially fraudulent and sensitive activity, including insider threats and snooping.
- Participate in an on-call rotation for responding to security incidents, internal questions and operational support.
- Work with the detection engineering team to develop new, high-fidelity detection rules based on incident trends and threat intelligence.
SKILLS YOU BRING
- 3+ years of experience in cybersecurity.
- 1–2+ years of hands-on incident response experience, owning investigations end to end.
- The ability to coordinate responders and stakeholders during an incident, and know when to escalate.
- Experience using a SIEM to turn noise into signal, including writing queries and tuning alerts.
- Proficiency with AI coding tools (Claude Code, Cursor, ChatGPT, etc.) to build and maintain automation. We invest in tooling (automation, Slack bots, AI agents) so responders spend their energy on the decisions that matter.
- A workflow mindset: you can look at a messy, recurring problem and break it into steps that tooling or AI can take on.
- Working knowledge of cloud infrastructure (e.g., AWS, GCP or Azure) and how to investigate within it.
- Discretion and sound judgment when handling sensitive information, such as HR and insider-threat matters.
- Clear, honest and inclusive communication with both internal and external stakeholders.
- Good judgment under pressure, in technical problem solving and in working across teams.
- A strong desire to learn from the team and others. We value making one another successful!
WHY WEALTHSIMPLE?
🌸 Top-tier health benefits and life insurance
📈 Long-term group savings with employer match, through Wealthsimple for Business
🌴 20 vacation days, 4 wellness days, and unlimited sick and mental health days per year*
✈️ 90 days away: work outside Canada for up to 90 days per year*
👥 Employee resource groups, including Rainbow (2SLGBTQ), Women of WS, and Black at WS
🌎 We are a hybrid team with over 1,500 employees across North America. The people are one of the best parts of working here: you'll collaborate with incredibly talented, curious, and driven teammates who are deeply committed to doing great work.
*Unlimited paid sick days, Wellness Days and the 90 day away program do not apply to certain roles.
ICYMI
Technology & Innovation at Wealthsimple: We move quickly and build thoughtfully. That means we're always looking for better ways to work — whether that's new tools, AI, or rethinking how we approach a problem. We don't expect you to have all the answers, but we do expect curiosity and a willingness to evolve alongside the products we're building.
Inclusion Statement: We're building products for a diverse world, and we need a diverse team to do it well. We strongly encourage applications from everyone, regardless of race, religion, colour, national origin, gender, sexual orientation, age, marital status, or disability status.
Accessibility Statement: We're committed to an accessible hiring experience. If you need any accommodations throughout the interview process, please let us know — we'll work with you to make sure you have what you need. We also welcome any feedback on how we can better accommodate candidates with accessibility needs.
AI in Hiring: We may use artificial intelligence (AI) tools to support parts of our hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our team but don't replace human judgment – all final hiring decisions are made by people. If you have questions about how your data is used, reach out to us.
Location: Ukraine; Spain; Slovakia; Serbia; Yerevan; Slovenia; Poland
Workplace: remote
Provectus is an AWS Premier Partner and an Anthropic Strategic Partner, working at the frontier of applied AI. We help enterprises turn Claude, agentic systems, and their own data into measurable business outcomes — through bespoke applications, managed services, and advisory engagements. With offices in North America, LATAM, and EMEA, we partner with clients worldwide.
Our work centers on two verticals — Financial Services & Insurance and Healthcare & Life Sciences — where we deploy five pre-built AI Blueprints: Submission Flow, Portfolio Lens, Asset Flow, Revenue Flow, and Evidence Lens. Each Blueprint rebuilds a critical business process front to back, shipped from working code and tuned to a client's specific book, regulators, and operating posture.
Our team holds 100+ AWS certifications, is Claude Code certified, and co-delivers Anthropic's Agentic SDLC program, Cowork Activation, and AI Blueprint engagements.
Where this role sits
You will work in a small, senior pod alongside an FDE and an FDX,
Forward Deployed Executives (FDX) own the commercial relationship and the business outcome. Works alongside the client's leadership or C-suite level to move the client's KPIs.
Forward Deployed Engineers (FDE) embed with a client, map the client workflow, identify the business problem underneath it, design and build a working AI solution, present to the client, and transfer the knowledge to the client's team. Owns technical direction of the whole solution.
Senior AI Engineer. When an FDE comes back from the client with the business problem, you will help turn that into an agentic system that runs in production and will be responsible for evaluation, observability, and guardrails. You'll have real ownership of components and of the technical decisions inside them.
Requirements:
Mindset
Proactive and self-directed; you push for clarity rather than waiting for a ticket
Excellent communication and problem-solving skills
Comfort with ambiguity and ownership.
B2+ English, comfortable collaborating across distributed, multicultural teams.
Technical depth
5+ years in software or ML engineering, with production systems you were accountable for.
Solid AI/ML foundations. You understand what the models do well enough to reason about failure modes.
Shipped to production LLM applications and agentic workflows — not demos, not POCs, not notebooks.
Agentic orchestration: multi-step workflows, graph-based orchestration, tool use, state management, and recovery from partial failure
Experience with LLM APIs (Anthropic, AWS Bedrock, or OpenAI) and agent frameworks.
Experience building and optimizing RAG systems in production.
Strong engineering fundamentals. Full-stack mindset, comfortable across AI, backend development, and cloud infrastructure. Python and/or TypeScript proficiency; depth matters more than stack. Dropped into an unfamiliar codebase, you're productive.
Hands-on AWS in production: Bedrock, Bedrock AgentCore, Lambda, ECS, S3, SQS, ECR, or similar. GCP or Azure is a plus.
Cloud-native delivery: containers, ECS or Kubernetes, IaC, and CI/CD applied to AI pipelines.
You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured, how you produced ground truth, and what gated a release.
Model and agent monitoring, drift detection.
Cost and latency discipline: model tiering, caching, and the ability to say what a workload costs to run before it runs.
Hands-on production experience with the Claude ecosystem — Claude Code, CLAUDE.md, hooks, skills files. Spec-driven development — writing the intent, constraints, and acceptance criteria before you let an agent build — is a strong plus.
MCP: you can say why an agent would prefer it to a REST integration. Having authored a server is a plus.
Nice to Have:
Experience in one of the industries: financial services, insurance, healthcare.
Consulting, professional services, or other embedded customer-facing delivery.
AWS and Claude Code Certifications
A2A: you can explain agent-to-agent interoperability
CI/CD pipeline experience (GitHub Actions, GitLab CI)
Practical experience with one or more use cases from the following: NLP, LLMs, and Recommendation engines.
Experience in an additional language (Go, TypeScript, or Rust).
Experience with Apache Spark, Apache Airflow, Kafkа
Responsibilities:
Work in a pair with an FDE and an FDX.
Build and ship production GenAI systems into the customer’s environment (cloud-native data, LLM-based, and agentic AI solutions).
Build and optimize RAG systems for production use cases
Build the evaluation harness before you build the feature.
Write production code across the stack — AI, backend services, data pipelines. We choose tools to fit the customer.
Integrate AI components into backend services and RESTful APIs
Take systems to production on AWS (GCP or Azure where the customer requires it): containerised, CI/CD. Implement LLMOps and AgentOps practices: agent tracing, prompt and version management, cost and latency monitoring, regression testing, drift detection
Start from the blueprint, contribute to enablement and handover: clear documentation, runbooks, and pairing with the client engineers who will inherit the system. Feed reusable components and lessons back into the Provectus Blueprints
Participate in technical discussions and architectural decisions
Conduct model evaluation, improve failure modes you find, optimize model performance, efficiency, and reliability
Mentor junior and mid-level AI engineers, conduct code reviews and share knowledge across the team through documentation, presentations, and workshops.
What We Offer:
The chance to shape how leading enterprises across LATAM, Europe, and North America adopt AI, from strategy through first deployment
A forward-deployed model working in small, senior teams alongside FDE and FDX
A growing AI delivery practice where you help build the tooling and frameworks, not just use them
Remote-friendly culture
Internal training programs with full support for Claude, AWS, and other professional certifications, conference attendance
Career growth; we actively develop our engineers
Access to the latest AI tools and premium subscriptions
Long-term B2B collaboration
Private medical insurance or a budget for your medical needs
Paid sick leave, vacation, and public holidays
Equipment and all the tech you need for comfortable, productive work
How we hire:
Intro conversation. The role, your background and aspirations, tech questions.
Technical interview with live engineering sessions. Real problems, your own editor, you may use an LLM assistant
HR Interview. Soft skills and expectations
HM interview. Tech questions; a live engineering session is also possible
Location: North Macedonia; Bosnia and Herzegovina; Czechia; Croatia; Moldova; Bulgaria; Montenegro
Workplace: remote
Provectus is an AWS Premier Partner and an Anthropic Strategic Partner, working at the frontier of applied AI. We help enterprises turn Claude, agentic systems, and their own data into measurable business outcomes — through bespoke applications, managed services, and advisory engagements. With offices in North America, LATAM, and EMEA, we partner with clients worldwide.
Our work centers on two verticals — Financial Services & Insurance and Healthcare & Life Sciences — where we deploy five pre-built AI Blueprints: Submission Flow, Portfolio Lens, Asset Flow, Revenue Flow, and Evidence Lens. Each Blueprint rebuilds a critical business process front to back, shipped from working code and tuned to a client's specific book, regulators, and operating posture.
Our team holds 100+ AWS certifications, is Claude Code certified, and co-delivers Anthropic's Agentic SDLC program, Cowork Activation, and AI Blueprint engagements.
Where this role sits
You will work in a small, senior pod alongside an FDE and an FDX,
Forward Deployed Executives (FDX) own the commercial relationship and the business outcome. Works alongside the client's leadership or C-suite level to move the client's KPIs.
Forward Deployed Engineers (FDE) embed with a client, map the client workflow, identify the business problem underneath it, design and build a working AI solution, present to the client, and transfer the knowledge to the client's team. Owns technical direction of the whole solution.
Senior AI Engineer. When an FDE comes back from the client with the business problem, you will help turn that into an agentic system that runs in production and will be responsible for evaluation, observability, and guardrails. You'll have real ownership of components and of the technical decisions inside them.
Requirements:
Mindset
Proactive and self-directed; you push for clarity rather than waiting for a ticket
Excellent communication and problem-solving skills
Comfort with ambiguity and ownership.
B2+ English, comfortable collaborating across distributed, multicultural teams.
Technical depth
5+ years in software or ML engineering, with production systems you were accountable for.
Solid AI/ML foundations. You understand what the models do well enough to reason about failure modes.
Shipped to production LLM applications and agentic workflows — not demos, not POCs, not notebooks.
Agentic orchestration: multi-step workflows, graph-based orchestration, tool use, state management, and recovery from partial failure
Experience with LLM APIs (Anthropic, AWS Bedrock, or OpenAI) and agent frameworks.
Experience building and optimizing RAG systems in production.
Strong engineering fundamentals. Full-stack mindset, comfortable across AI, backend development, and cloud infrastructure. Python and/or TypeScript proficiency; depth matters more than stack. Dropped into an unfamiliar codebase, you're productive.
Hands-on AWS in production: Bedrock, Bedrock AgentCore, Lambda, ECS, S3, SQS, ECR, or similar. GCP or Azure is a plus.
Cloud-native delivery: containers, ECS or Kubernetes, IaC, and CI/CD applied to AI pipelines.
You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured, how you produced ground truth, and what gated a release.
Model and agent monitoring, drift detection.
Cost and latency discipline: model tiering, caching, and the ability to say what a workload costs to run before it runs.
Hands-on production experience with the Claude ecosystem — Claude Code, CLAUDE.md, hooks, skills files. Spec-driven development — writing the intent, constraints, and acceptance criteria before you let an agent build — is a strong plus.
MCP: you can say why an agent would prefer it to a REST integration. Having authored a server is a plus.
Nice to Have:
Experience in one of the industries: financial services, insurance, healthcare.
Consulting, professional services, or other embedded customer-facing delivery.
AWS and Claude Code Certifications
A2A: you can explain agent-to-agent interoperability
CI/CD pipeline experience (GitHub Actions, GitLab CI)
Practical experience with one or more use cases from the following: NLP, LLMs, and Recommendation engines.
Experience in an additional language (Go, TypeScript, or Rust).
Experience with Apache Spark, Apache Airflow, Kafkа
Responsibilities:
Work in a pair with an FDE and an FDX.
Build and ship production GenAI systems into the customer’s environment (cloud-native data, LLM-based, and agentic AI solutions).
Build and optimize RAG systems for production use cases
Build the evaluation harness before you build the feature.
Write production code across the stack — AI, backend services, data pipelines. We choose tools to fit the customer.
Integrate AI components into backend services and RESTful APIs
Take systems to production on AWS (GCP or Azure where the customer requires it): containerised, CI/CD. Implement LLMOps and AgentOps practices: agent tracing, prompt and version management, cost and latency monitoring, regression testing, drift detection
Start from the blueprint, contribute to enablement and handover: clear documentation, runbooks, and pairing with the client engineers who will inherit the system. Feed reusable components and lessons back into the Provectus Blueprints
Participate in technical discussions and architectural decisions
Conduct model evaluation, improve failure modes you find, optimize model performance, efficiency, and reliability
Mentor junior and mid-level AI engineers, conduct code reviews and share knowledge across the team through documentation, presentations, and workshops.
What We Offer:
The chance to shape how leading enterprises across LATAM, Europe, and North America adopt AI, from strategy through first deployment
A forward-deployed model working in small, senior teams alongside FDE and FDX
A growing AI delivery practice where you help build the tooling and frameworks, not just use them
Remote-friendly culture
Internal training programs with full support for Claude, AWS, and other professional certifications, conference attendance
Career growth; we actively develop our engineers
Access to the latest AI tools and premium subscriptions
Long-term B2B collaboration
Private medical insurance or a budget for your medical needs
Paid sick leave, vacation, and public holidays
Equipment and all the tech you need for comfortable, productive work
How we hire:
Intro conversation. The role, your background and aspirations, tech questions.
Technical interview with live engineering sessions. Real problems, your own editor, you may use an LLM assistant
HR Interview. Soft skills and expectations
HM interview. Tech questions; a live engineering session is also possible
Location: Ukraine; Serbia; Yerevan; Spain; Slovakia; Slovenia; Poland
Workplace: remote
Provectus is an AWS Premier Partner and an Anthropic Strategic Partner, working at the frontier of applied AI. We help enterprises turn Claude, agentic systems, and their own data into measurable business outcomes — through bespoke applications, managed services, and advisory engagements. With offices in North America, LATAM, and EMEA, we partner with clients worldwide.
Our work centers on two verticals — Financial Services & Insurance and Healthcare & Life Sciences — where we deploy five pre-built AI Blueprints: Submission Flow, Portfolio Lens, Asset Flow, Revenue Flow, and Evidence Lens. Each Blueprint rebuilds a critical business process front to back, shipped from working code and tuned to a client's specific book, regulators, and operating posture.
Our team holds 100+ AWS certifications, is Claude Code certified, and co-delivers Anthropic's Agentic SDLC program, Cowork Activation, and AI Blueprint engagements.
Where this role sits
You will work in a small, senior pod alongside an FDX; our delivery arc is Sprint → Enable → Realize:
Forward Deployed Executive (FDX) owns the commercial relationship and the business outcome. Works alongside the client's leadership or C-suite level to move the client's KPIs — revenue growth, cost reduction, risk reduction.
Forward Deployed Engineer (FDE) embeds with a client to change how that client operates. You own the method; nobody hands you a ticket. You map the client workflow as it actually happens, identify the business problem underneath it, build a working AI solution, present to the client in the language of outcomes, and transfer it. Provectus maintains industry Blueprints — working systems that have already shipped for a client in the same industry — so you begin from running code and tuning it to this client's specific book, regulators, and operating posture. You will be measured on whether the Business Unit's number moved, not on hours or scope delivered.
What You’ll Do:
Take the seat
Sit with the client and the Forward Deployed Executive at the start of an engagement. Learn the function from inside, not from a requirements doc, and redesign the function from first principles.
Reach working fluency in a new domain — insurance underwriting, healthcare revenue cycle, asset flow.
Build
Design and ship production GenAI systems into the customer’s environment (cloud-native data, LLM-based, and agentic AI solutions). Implement and optimize RAG systems for production use cases
Build the evaluation harness before you build the feature. Define what working means, instrument it, and let the evals drive the design.
Write production code across the stack — AI, backend services, data pipelines. We choose tools to fit the customer.
Take systems to production on AWS (GCP or Azure where the customer requires it): containerised, CI/CD, automated testing, monitoring, and maintainable after we leave. Hand the system over to the client.
Start from the blueprint, and feed the blueprint. What you learn in the field becomes the baseline the next engagement starts from.
Lead architecture reviews, produce technical design documents, and contribute to standards. Mentor engineers and share knowledge across the team.
Own the outcome.
Work in a pair with a FDX who carries the Business Unit’s KPIs. Your work is measured against the same number.
Own the technical direction of technical proposals and scoping. Drive adoption. Change management is part of the engineering job here.
Be credible with the customer’s engineers and their executives.
Shape what we commit to before we commit to it.
What You’ll Bring:
Mindset
Proactive and self-directed; identify problems before they're handed to you
Comfort with ambiguity and ownership. Engagements start underspecified by design. Closing that gap is the job
B2+ English, comfortable collaborating across distributed, multicultural teams
Client Engagement
You are willing to spend time understanding and doing someone else’s job on the client's side before you write a line of code
Credible with senior stakeholders — you can hold a redesign conversation with a BU head and a scoping conversation with a CTO, presenting outcomes to them
You can produce a scoped, phased delivery plan with clear deliverables, dependencies, and risks — and estimate what it will cost to build and to run
Technical depth
7+ years building and running production systems.
Solid AI/ML foundations. You understand what the models do well enough to reason about failure modes
Designed and shipped to production LLM applications and agentic workflows — not demos, not POCs, not notebooks
Agentic orchestration: multi-step workflows, graph-based orchestration, tool use, state management, and recovery from partial failure
Experience with LLM APIs (Anthropic, AWS Bedrock, or OpenAI) and agent frameworks.
Experience building and optimizing RAG systems in production
Strong engineering fundamentals — dropped into an unfamiliar codebase or language, you’re productive. Python and/or TypeScript proficiency; depth matters more than stack.
Experience in making and defending architectural trade-off decisions
Hands-on AWS production depth: Bedrock, Bedrock AgentCore, Lambda, ECS, S3, SQS, ECR, or similar. GCP or Azure is a plus
Cloud-native delivery: containers, ECS or Kubernetes, IaC, and CI/CD applied to AI pipelines
You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured, how you produced ground truth, and what gated a release
Model and agent monitoring, drift detection
Cost and latency discipline: model tiering, caching, and the ability to say what a workload costs to run before it runs
Hands-on production experience with the Claude ecosystem — Claude Code, CLAUDE.md, hooks, skills files. Spec-driven development — writing the intent, constraints, and acceptance criteria before you let an agent build — is a strong plus
MCP: you can say why an agent would prefer it to a REST integration. Having authored a server is a plus
Nice to have:
Prior experience as a founder, CTO, or engineering leader who has chosen to return to individual contribution
Experience in one of the industries: financial services, insurance, healthcare
Consulting, professional services, or other embedded customer-facing delivery
A2A: you can explain agent-to-agent interoperability
AWS and Claude Code Certifications
CI/CD pipeline experience (GitHub Actions, GitLab CI)
Experience in an additional language (Go, TypeScript, or Rust)
Experience with Apache Spark, Apache Airflow, Kafkа
What We Offer:
The chance to shape how leading enterprises across LATAM, Europe, and North America adopt AI, from strategy through first deployment
A forward-deployed model working in small, senior teams alongside Principal Architects and Forward Deployed Engineers
A growing AI delivery practice where you help build the tooling and frameworks, not just use them
Remote-friendly culture
Internal training programs with full support for Claude, AWS, and other professional certifications, conference attendance
Career growth; we actively develop our engineers
Access to the latest AI tools and premium subscriptions
Long-term B2B collaboration
Private medical insurance or a budget for your medical needs
Paid sick leave, vacation, and public holidays
Equipment and all the tech you need for comfortable, productive work
How we hire:
Intro conversation. The role, your background and aspirations, tech questions.
Technical interview with live engineering sessions. Real problems, your own editor, you may use an LLM assistant
HR Interview. Soft skills and expectations
HM interview. Tech questions; a live engineering session is also possible
Location: North Macedonia; Montenegro; Moldova; Bulgaria; Czechia; Bosnia and Herzegovina; Croatia
Workplace: remote
Provectus is an
AWS Premier Partner
and an
Anthropic Strategic Partner
, working at the frontier of applied AI. We help enterprises turn Claude, agentic systems, and their own data into measurable business outcomes — through bespoke applications, managed services, and advisory engagements. With offices in North America, LATAM, and EMEA, we partner with clients worldwide.
Our work centers on two verticals —
Financial Services & Insurance
and
Healthcare & Life Sciences
— where we deploy five pre-built AI Blueprints: Submission Flow, Portfolio Lens, Asset Flow, Revenue Flow, and Evidence Lens. Each Blueprint rebuilds a critical business process front to back, shipped from working code and tuned to a client's specific book, regulators, and operating posture.
Our team holds 100+ AWS certifications, is Claude Code certified, and co-delivers Anthropic's Agentic SDLC program, Cowork Activation, and AI Blueprint engagements.
Where this role sits
You will work in a small, senior pod alongside an FDX; our delivery arc is Sprint → Enable → Realize:
Forward Deployed Executive (FDX) owns the commercial relationship and the business outcome. Works alongside the client's leadership or C-suite level to move the client's KPIs — revenue growth, cost reduction, risk reduction.
Forward Deployed Engineer (FDE) embeds with a client to change how that client operates. You own the method; nobody hands you a ticket. You map the client workflow as it actually happens, identify the business problem underneath it, build a working AI solution, present to the client in the language of outcomes, and transfer it. Provectus maintains industry Blueprints — working systems that have already shipped for a client in the same industry — so you begin from running code and tuning it to this client's specific book, regulators, and operating posture. You will be measured on whether the Business Unit's number moved, not on hours or scope delivered.
What You’ll Do:
Take the seat
Sit with the client and the Forward Deployed Executive at the start of an engagement. Learn the function from inside, not from a requirements doc, and redesign the function from first principles.
Reach working fluency in a new domain — insurance underwriting, healthcare revenue cycle, asset flow.
Build
Design and ship production GenAI systems into the customer’s environment (cloud-native data, LLM-based, and agentic AI solutions). Implement and optimize RAG systems for production use cases
Build the evaluation harness before you build the feature. Define what working means, instrument it, and let the evals drive the design.
Write production code across the stack — AI, backend services, data pipelines. We choose tools to fit the customer.
Take systems to production on AWS (GCP or Azure where the customer requires it): containerised, CI/CD, automated testing, monitoring, and maintainable after we leave. Hand the system over to the client.
Start from the blueprint, and feed the blueprint. What you learn in the field becomes the baseline the next engagement starts from.
Lead architecture reviews, produce technical design documents, and contribute to standards. Mentor engineers and share knowledge across the team.
Own the outcome.
Work in a pair with a FDX who carries the Business Unit’s KPIs. Your work is measured against the same number.
Own the technical direction of technical proposals and scoping. Drive adoption. Change management is part of the engineering job here.
Be credible with the customer’s engineers and their executives.
Shape what we commit to before we commit to it.
What You’ll Bring:
Mindset
Proactive and self-directed; identify problems before they're handed to you
Comfort with ambiguity and ownership. Engagements start underspecified by design. Closing that gap is the job
B2+ English, comfortable collaborating across distributed, multicultural teams
Client Engagement
You are willing to spend time understanding and doing someone else’s job on the client's side before you write a line of code
Credible with senior stakeholders — you can hold a redesign conversation with a BU head and a scoping conversation with a CTO, presenting outcomes to them
You can produce a scoped, phased delivery plan with clear deliverables, dependencies, and risks — and estimate what it will cost to build and to run
Technical depth
7+ years building and running production systems.
Solid AI/ML foundations. You understand what the models do well enough to reason about failure modes
Designed and shipped to production LLM applications and agentic workflows — not demos, not POCs, not notebooks
Agentic orchestration: multi-step workflows, graph-based orchestration, tool use, state management, and recovery from partial failure
Experience with LLM APIs (Anthropic, AWS Bedrock, or OpenAI) and agent frameworks.
Experience building and optimizing RAG systems in production
Strong engineering fundamentals — dropped into an unfamiliar codebase or language, you’re productive. Python and/or TypeScript proficiency; depth matters more than stack.
Experience in making and defending architectural trade-off decisions
Hands-on AWS production depth: Bedrock, Bedrock AgentCore, Lambda, ECS, S3, SQS, ECR, or similar. GCP or Azure is a plus
Cloud-native delivery: containers, ECS or Kubernetes, IaC, and CI/CD applied to AI pipelines
You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured, how you produced ground truth, and what gated a release
Model and agent monitoring, drift detection
Cost and latency discipline: model tiering, caching, and the ability to say what a workload costs to run before it runs
Hands-on production experience with the Claude ecosystem — Claude Code, CLAUDE.md, hooks, skills files. Spec-driven development — writing the intent, constraints, and acceptance criteria before you let an agent build — is a strong plus
MCP: you can say why an agent would prefer it to a REST integration. Having authored a server is a plus
Nice to have:
Prior experience as a founder, CTO, or engineering leader who has chosen to return to individual contribution
Experience in one of the industries: financial services, insurance, healthcare
Consulting, professional services, or other embedded customer-facing delivery
A2A: you can explain agent-to-agent interoperability
AWS and Claude Code Certifications
CI/CD pipeline experience (GitHub Actions, GitLab CI)
Experience in an additional language (Go, TypeScript, or Rust)
Experience with Apache Spark, Apache Airflow, Kafkа
What We Offer:
The chance to shape how leading enterprises across LATAM, Europe, and North America adopt AI, from strategy through first deployment
A forward-deployed model working in small, senior teams alongside Principal Architects and Forward Deployed Engineers
A growing AI delivery practice where you help build the tooling and frameworks, not just use them
Remote-friendly culture
Internal training programs with full support for Claude, AWS, and other professional certifications, conference attendance
Career growth; we actively develop our engineers
Access to the latest AI tools and premium subscriptions
Long-term B2B collaboration
Private medical insurance or a budget for your medical needs
Paid sick leave, vacation, and public holidays
Equipment and all the tech you need for comfortable, productive work
How we hire:
Intro conversation. The role, your background and aspirations, tech questions.
Technical interview with live engineering sessions. Real problems, your own editor, you may use an LLM assistant
HR Interview. Soft skills and expectations
HM interview. Tech questions; a live engineering session is also possible
Location: US - Headquarters - Maryland - Columbia
Who is Tenable?
Tenable® is the Exposure Management company. Over 40,000 organizations around the globe rely on Tenable to understand and reduce cyber risk. Our global employees support 65 percent of the Fortune 500, 50 percent of the Global 2000, and large government agencies. Come be part of our journey!
What makes Tenable such a great place to work?
Ask a member of our team and they’ll answer, “Our people!” We work together to build and innovate best-in-class cybersecurity solutions for our customers; all while creating a culture of belonging, respect, and excellence where we can be our best selves. When you’re part of our #OneTenable team, you can expect to partner with some of the most talented and passionate people in the industry, and have the support and resources you need to do work that truly matters. We deliver results that exceed expectations and we win together!
Your Role:
As an AI Security Engineer on Tenable's Information Security team, you will help shape and mature our approach to securing AI both within Tenable's products and across the enterprise. AI introduces a new class of risk at the intersection of application security, cloud risk, and data governance, and you will be on the front lines of defining how we assess, test, and address it.
You will apply hands-on AI engineering experience alongside product security and application security skills to design security controls for AI systems, lead assessments, and help engineering teams ship AI features securely. You will establish security standards for responsible AI use, influence decisions across the organization, and build tooling that raises our security posture.
This role is ideal for a practitioner who has spent time building or tinkering with AI systems, looking under the hood of model internals, and wants to channel that experience into a security specialty.
Your Opportunity:
Design, implement, and maintain end-to-end security controls across the AI/ML lifecycle.
Assist in the implementation of robust security guardrails, controls, and boundary mechanisms for Large Language Models (LLMs), Small Language Models (SLMs), and open-source models.
Continuously monitor the AI landscape for novel vulnerabilities and attack techniques, applying deep engineering experience to proactively defend enterprise AI deployments.
Assist in developing security reference architectures for AI deployment patterns, including MCP servers and agentic AI workflows and harnesses.
Deploy controls to ensure model integrity, governance, and proper access control across models and feature stores.
Build AI-driven tooling to strengthen cybersecurity posture across identity, incident management, vulnerability management, third-party risk, and emerging AI threat vectors.
Perform AI safety, security assessments, threat modeling for AI/ML systems, identifying risks such as data poisoning, model evasion, model extraction, adversarial inputs, and integrity attacks.
Collaborate with software engineers, and product teams to integrate security best practices into AI development, training, validation, and deployment processes.
Create security guidance, documentation, and training for internal engineering and development teams; develop metrics that drive desired security behaviors and outcomes.
Assist in researching emerging trends in AI security and contribute to innovative solutions that support Tenable's AI initiatives.
What You'll Need:
2 or more years of professional experience in information security or application security, with at least a demonstrated interest on securing AI/ML systems.
Bachelor’s Degree in Computer Science, Cybersecurity, Data Science, or a related field preferred.
Awareness of AI-specific security threats, including adversarial ML, data poisoning, prompt injection, model inversion, model evasion, and inference attacks.
Knowledge of data security principles, including encryption, masking, and tokenization.
Knowledge of SSDLC, DevSecOps, and security testing practices, including SAST, DAST, SCA, and threat modeling.
Knowledge of application security architecture best practices and patterns, including modern web applications, Docker, and microservices.
Ability to work cross-functionally across engineering, product, and business teams.
Strong written and verbal communication skills; able to clearly translate complex AI security risks for both technical and non-technical audiences.
Strong problem-solving skills, attention to detail, and ability to lead projects with end-to-end ownership.
Self-motivated and effective working independently and across distributed teams.
And Ideally:
Hands-on experience with AI red teaming, adversarial prompt testing, or LLM security assessments.
Basic coding experience in Python and/or Go.
Experience with frameworks & libraries such as PyTorch, Hugging Face Transformers, TensorFlow or similar.
Strong understanding of the ML/AI lifecycle and the security risks associated with each stage.
Experience with application security assessment tools (Burp Suite, ZAP, Tenable WAS, etc.)
Knowledge of cloud security platforms: AWS, Azure, or GCP including AI/ML-related services.
Security certifications: CISSP, CSSLP, SANS GIAC, CEH, or AI-focused security certifications are a plus, but not necessary.
#LI-Hybrid
#LI-MS1
This is the base pay range for this position. Compensation for the role will depend on a number of factors, including the candidate's qualifications, skills, competencies, location and experience, and may fall outside of the range shown. Employees are also eligible for variable compensation in addition to base pay (commission for sales roles, bonus for non-sales roles), depending on company and individual performance. Tenable also offers a variety of comprehensive and competitive benefits which include: medical, dental, vision, disability and life insurance; 401(k) retirement savings with company match; an employee stock purchase plan; an employee referral program; flexible spending accounts; an Employee Assistance Program (EAP); education assistance; parental leave; paid time off (PTO); company-paid holidays; health and wellness events; and community programs.
US Pay Range
$102,500
—
$136,500 USD
We’re committed to promoting Equal Employment Opportunity (EEO) at Tenable - through all equal employment opportunity laws and regulations at the international, federal, state and local levels. If you need a reasonable accommodation due to a disability during the application or recruiting process, please contact
Recruiting@Tenable.com
for further assistance.
Tenable Data Consent Statement
Tenable is committed to protecting the privacy and security of your personal data. Depending on your location, one or more of the following notices may apply to you:
General Applicant Privacy Notice
California Applicant Privacy Notice
EU/EEA/UK Applicant Privacy Notice
Location: Remote - United Kingdom
Who we are
At Twilio, we’re shaping the future of communications, all from the comfort of our homes. We deliver innovative solutions to
hundreds of thousands of businesses
and empower millions of developers worldwide to craft personalized customer experiences.
Our dedication to
remote-first work
, and strong culture of connection and global inclusion means that no matter your location, you’re part of a vibrant team with diverse experiences making a global impact each day. As we continue to revolutionize how the world interacts, we’re acquiring new skills and experiences that make work feel truly rewarding. Your career at Twilio is in your hands.
.
Hiring and how we work
We use Artificial Intelligence (AI) to help make our hiring process efficient. That said, every hiring decision is made by real Twilions!
Also, while we are a remote-first company, you may be asked to report in person on an ad-hoc basis for team gatherings, functional off-sites or customer meetings.
.
See yourself at Twilio
Join us as our next Senior Solutions Engineer on Twilio’s Digital Sales Communications team!
About the job
This position is needed to enable our customers to build the future of communications. The Senior Solutions Engineer is a critical part of the sales team focused on our Digital Sales segment.
Twilio’s Senior Solutions Engineers are responsible for delivering the technical win and best product fit to our customers.They lead the technical pre-sales relationship, drive technical discovery, propose technical architectures, demonstrate the product, anticipate concerns and offer creative solutions. They build customer trust in Twilio’s solutions.
Responsibilities
In this role, you’ll:
Partner with Account Executives to execute pre-sales activities including opportunity qualification, demonstrations, Proof-of-Concept, RFP, design documentation, technical presentations and enablement sessions.
Help customers achieve success by leading the technical and product sale, recommending best-practice solutions, and guiding them on how to use Twilio’s APIs.
Establish yourself as a trusted advisor to our customers, by taking the lead on understanding customer technical pains through discovery in order to design, demonstrate, and present innovative solutions that solve business challenges.
Build and present highly interactive, complex and engaging customer product demonstrations to help showcase the capabilities of Twilio’s Communications Products, while effectively forming strong customer relationships with both technical and nontechnical stakeholders.
Be Hands-on, high-energy, passionate, and a creative problem solver, equipped with the knowledge of how to get things done and ability to lead others to success.
Take the initiative to identify and solve problems - both for the customer and within the organization as we grow.
Contribute to the broader Twilio Solutions Engineering community through knowledge sharing, constructing demonstration materials, and creating reusable presentations.
Qualifications
Twilio values diverse experiences from all kinds of industries, and we encourage everyone who meets the required qualifications to apply. If your career is just starting or hasn't followed a traditional path, don't let that stop you from considering Twilio. We are always looking for people who will bring something new to the table!
*Required:
5+ years of pre-sales experience selling complex, technical products or 3+ years of professional experience supporting technical products coupled with customer facing experience, particularly in delivery or consulting.
Excellent communicator and presenter able to gain audience confidence.
An engaging storyteller - you can gain audience confidence and communicate complex topics to multiple levels of audience.
Ability to build a deep understanding of a customer’s communications needs and guide them to a technical solution.
Previous software development experience or working knowledge in one or more of the following areas:
Backend (Java, C#, Node.js, Python, PHP)
Web development (JavaScript, HTML/CSS, frontend frameworks - React, Vue.js, Angular)
Experience building with REST APIs
Bachelor’s and/or Master’s degree in a technical discipline (Engineering, Mathematics, Computer Science) or equivalent practical experience.
Desired:
Familiarity with cloud platforms (Amazon Web Services, Google Cloud, Microsoft Azure) and cloud application architecture.
Previous experience in Telecom, SIP, Contact Center, or Security is a plus.
Experience with sales methodologies.
Location
This role will be remote AND based in the United Kingdom.
Travel
We prioritize connection and opportunities to build relationships with our customers and each other. For this role, approximately 10% travel is anticipated to help you connect in-person in a meaningful way.
What We Offer
Working at Twilio offers many benefits, including competitive pay, generous time off, ample parental and wellness leave, healthcare, a retirement savings program, and much more. Offerings vary by location.
Twilio thinks big. Do you?
We like to solve problems, take initiative, pitch in when needed, and are always up for trying new things. That's why we seek out colleagues who embody our values — something we call
Twilio Magic
. Additionally, we empower employees to build
positive change in their communities
by supporting their volunteering and donation efforts.
So, if you're ready to unleash your full potential, do your best work, and be the best version of yourself, apply now! If this role isn't what you're looking for,
please consider other open positions.
.
Stay alert to recruitment fraud
We care about your safety. Scammers sometimes impersonate Twilio recruiters through fake job postings, emails, websites, or messages. Please ensure you are engaging with an official @
twilio.com
email address. We will never ask for payment, gift cards, cryptocurrency, or banking information during the recruiting process. We do not make job offers without a formal interview process or conduct interviews exclusively through text-based messaging apps.
.
Twilio is proud to be an equal opportunity employer.
We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Qualified applicants with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Additionally, Twilio participates in the E-Verify program in certain locations, as required by law.
Ищут старшего геймдизайнера в midcore-проект. Будете вести фичи полным циклом от концепта до релиза, ставить задачи команде вместе с продюсером, оценивать сроки и отвечать за результат в своей зоне.
УдалённоseniorМы ищем аккуратно: без массовых рассылок, только в студии, которые вам подходят, и сами ведём переписку с рекрутерами, пока вы работаете
🕹 Список обязанностей: — Определять и реализовывать стратегии инфраструктуры и кибербезопасности, технологические роадмапы, архитектурные стандарты, операционные процедуры и лучшие инженерные практики в соответствии с бизнес-целями банка.
ОфисseniorПномпень; Вакансия предполагает релокацию, предоставляется релокационный пакет и жилье; 🕹 Примерный уровень ЗП: $12 000 gross 🕹 Условия работы: — full-time — Релокационный пакет и жильё гарантируются 🕹 Контакты: @VolkTat_7941
• Разработка стратегии и целевой архитектуры мобильных и цифровых каналов банка. • Руководство, развитие и масштабирование команды мобильной разработки.
ОфисheadПномпень; Камбоджа | Офис | Релокация и жильё оплачиваются
Location: Bucharest
Workplace: OnSite
LIFE AT UIPATH
The people at UiPath believe in the transformative power of automation to change how the world works. We’re committed to creating category-leading enterprise software that unleashes that power.
To make that happen, we need people who are curious, self-propelled, generous, and genuine. People who love being part of a fast-moving, fast-thinking growth company. And people who care—about each other, about UiPath, and about our larger purpose.
Could that be you?
YOUR MISSION
As a Principal Software Engineer on the LLM Gateway team, you will set the technical direction of UiPath’s AI Trust Layer: the gateway through which every UiPath product, and every agent our customers build, reaches models from OpenAI, Anthropic, Google and other commercial and open-weight providers. You will lead the architecture of a secure, globally distributed, high-throughput proxy serving text, image, voice and emerging modalities, with intelligent routing, rate limiting and cost controls, running the same way in our public cloud, in government and sovereign clouds, and in customer-hosted deployments. You will own the LLM infrastructure behind it: sourcing and balancing model capacity across vendors, tiers and regions, with data residency guaranteed in every geography. You will also own how customers see and control AI in their organizations: which models their users and automations can access, including the models they bring themselves, under what conditions, and with what policies, data protection and audit trail. You will raise the engineering bar of the team, work closely with product teams, security, legal and our model vendors, and help shape how we build software with AI agents.
WHAT YOU'LL DO AT UIPATH
- Lead the architecture and technical direction of complex backend and cloud-native services across the UiPath platform.
- Design scalable, secure, reliable, and high-performing distributed systems across cloud, on-premises, and hybrid environments.
- Partner with engineering leaders, architects, product managers, and cross-functional teams to shape technical solutions for high-impact product and platform areas.
- Drive technical planning and roadmap input for complex services, platform capabilities, or cross-team initiatives.
- Identify long-term scalability, reliability, security, performance, and cost challenges, and lead the design of sustainable solutions.
- Set high standards for system design, code quality, testing, observability, automation, incident management, and engineering excellence.
- Mentor and guide engineers through design reviews, technical discussions, architecture decisions, and hands-on technical feedback.
WHAT YOU'LL BRING TO THE TEAM
- 7+ years of software engineering experience, with strong backend and cloud development experience.
- Hands-on experience with one or more modern programming languages such as C#, Java, Python, or Go.
- Strong experience designing and building distributed systems, microservices, APIs, and cloud-native architectures.
- Proven ability to influence technical direction and drive architecture decisions across teams.
- Experience building and operating production-grade services in cloud environments such as Azure, AWS, or GCP.
- Good knowledge of containers, Kubernetes, CI/CD, monitoring, logging, observability, and production operations.
- Strong understanding of system design, data structures, algorithms, multithreading, asynchronous programming, and performance optimization.
- Experience with relational and/or NoSQL databases, messaging systems, event-driven architectures, or high-scale data processing.
- Ability to balance customer experience, reliability, security, scalability, and cloud cost when making technical decisions.
- Strong technical leadership, ownership, and communication skills, with the ability to guide teams through ambiguity.
- Interest in automation, AI, developer platforms, enterprise software, or large-scale cloud systems is a plus.
Maybe you don’t tick all the boxes above—but still think you’d be great for the job? Go ahead, apply anyway. Please. Because we know that experience comes in all shapes and sizes—and passion can’t be learned.
Many of our roles allow for flexibility in when and where work gets done. Depending on the needs of the business and the role, the number of hybrid, office-based, and remote workers will vary from team to team. Applications are assessed on a rolling basis and there is no fixed deadline for this requisition. The application window may change depending on the volume of applications received or may close immediately if a qualified candidate is selected.
We value a range of diverse backgrounds, experiences and ideas. We pride ourselves on our diversity and inclusive workplace that provides equal opportunities to all persons regardless of age, race, color, religion, sex, sexual orientation, gender identity, and expression, national origin, disability, neurodiversity, military and/or veteran status, or any other protected classes. Additionally, UiPath provides reasonable accommodations for candidates on request and respects applicants' privacy rights. To review these and other legal disclosures, visit our privacy policy https://www.uipath.com/legal/trust-and-security/privacy-policy.
Location: Yerevan, Armenia
Workplace: hybrid
TeamViewer provides a leading Digital Workplace platform that connects people with technology—enabling, improving and automating digital processes to make work work better. Our software solutions harness the power of AI and shape the future of digitalization.
We believe that our diverse teams and strong company culture are key to the success of our products and technologies, that hundreds of millions of users around the world and around 645,000 customers across all industries rely on. With more than 1,900 employees worldwide, we celebrate the unique perspectives and talents that each individual brings to the table and foster a dynamic work environment where new ideas thrive. Are you ready to join our team and make an impact?
Responsibilities
We are looking for a QA Engineer (all genders) to actively contribute to manual testing as well as driving test automation for our products.
Write, review and execute test plans and test cases throughout the development life cycle
Ensure test plans thoroughly cover all requirements and customer use cases
Develop automated tests for the most important test suites and set them up under CI/CD
Actively participate in refinement sessions of the team and provide feedback from the end-user perspective
Closely work with QAs from other teams on common topics (e.g., test strategy, tooling, best practices)
Foster a continuous improvement approach to QA activities
Monitor, troubleshoot and maintain daily automated regression runs
Requirements
A university or college degree in Computer Science, Information Technology, or a similar subject is required
At least 5 years of experience in manual and automation testing is required
Proven skills and working history in designing and implementing automated tests (including test planning, maintenance, and reporting)
Solid understanding of software testing fundamentals (test design techniques, defect lifecycle, root cause analysis)
Good operating system knowledge, including troubleshooting and working with at least one desktop OS (Windows, macOS) and/or Linux at an advanced level (command line basics, logs, processes, networking basics)
Test management: TestRail (or similar)
Automation frameworks/tools: Ranorex or Selenium (C#)
CI/CD: Experience integrating automated tests into CI pipelines (e.g., Jenkins, GitHub Actions, GitLab CI, Azure DevOps)
Fluency in English is mandatory; additional languages are a plus
What we offer
The work location is our office in Yerevan, Armenia
Onsite Onboarding in our HQ office for an optimal start
Great compensation and benefits packages including company achievement bonus and regular salary reviews
Access to Corporate Benefits platform with many discounts
Regular Team events and company-wide celebrations
Public transport-friendly office
E-car charger at our parking
Monthly breakfast
Open door policy, no dress code rules, frequent all-hands
Hybrid work time with up to 50% home office
We celebrate diversity as one of our core values, and join and drive one of the c-a-r-e initiatives together with us!
TeamViewer is an equal opportunities employer and is committed to building an inclusive culture where everyone feels welcome and supported. We C-A-R-E and understand that our diverse, values-driven culture makes us stronger. As we continue to grow as a company, we also focus on enabling our employees to grow both personally and professionally. We are proud to have an open and embracing workplace environment that will empower you to be your best no matter your gender, civil or family status, sexual orientation, religion, age, disability, education level, or race.
If you require any accommodations or adjustments during the application or hiring process, including interview or onboarding support, please reach out to your Talent Acquisition Partner, who will be happy to support you.
seniorUnited States; Relocation assistance is not provided
УдалённоseniorГеография найма не уточнена
Не хотите искать каждый день?
Настройте подбор один раз, и подходящие вакансии будут сами приходить в Telegram.
Настройте подбор, и подходящие вакансии будут приходить в Telegram.
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