AI Labs Armenia Talk

Talent

Senior engineers who can own real systems.

Illustrative roles we place regularly. In real engagements, you review specific backgrounds, work samples (where permissible), and interview for your stack—not a generic "AI developer" label.

Senior-only bench
Five-plus years shipping production systems—no juniors padded into proposals.
AI-native fluency
Working knowledge of LLMs, retrieval, evals, and the rest of the modern stack.
Owners, not seat-fillers
Engineers who write specs, run reviews, and stay until the work is shipped.

Example profiles

Representative engineers from our bench.

Not stock biographies—each profile is shaped from real seniors we have placed. Specific matches for your roadmap come after the discovery call.

Staff ML Engineer

LLM applications · evaluation · Python/Go

Vetted

Former lead on customer-facing copilots; ships retrieval stacks, eval suites, and guardrails with measurable quality bars.

  • PyTorch
  • OpenAI API
  • K8s

Senior MLOps Engineer

Serving · CI/CD for models · observability

Vetted

Builds reproducible training and release pipelines; treats model rollouts with the same rigour as software releases.

  • Terraform
  • Prometheus
  • Ray

Senior Data Engineer

Streaming · warehouse · feature pipelines

Vetted

Designs data foundations that keep ML features fresh and auditable—without turning your lake into chaos.

  • Kafka
  • Snowflake
  • dbt

Full-stack AI Product Engineer

TypeScript · product UX · model UX

Vetted

Bridges design and model behaviour: crisp UX for uncertain outputs, resilient loading states, and thoughtful human review.

  • React
  • Node
  • Postgres

Roles we place regularly

The shapes most teams need—covered by senior people.

AI-heavy work rarely lives in one role. We staff across the surface so a single engagement can cover modelling, platform, data, and the product layer that ships it to users.

  • AI / ML

    Applied ML, LLM applications, retrieval, evaluation, agents, MLOps, computer vision, NLP.

  • Backend & platform

    TypeScript / Python / Go services, cloud-native infrastructure, event systems, security-aware foundations.

  • Frontend & full-stack

    React, Next.js, Astro—product engineers who pair model behaviour with crisp, accessible UX.

  • Data engineering

    Streaming, warehousing, feature pipelines, semantic layers—the ML/AI dependencies usually under-staffed.

  • Product design

    Senior designers who understand AI UX patterns, evaluation surfaces, and human-in-the-loop tooling.

  • Engineering leadership

    Tech leads, principals, and fractional leads to anchor a workstream or harden review and delivery practice.

How matching works

From brief to senior engineers in your repo.

Most teams move from first email to engineers shipping in three to five weeks—dictated mostly by your interview pace, not ours.

  1. 01

    Tell us the gap

    Send the role(s), stack, engagement model, timezone, and any compliance constraints. Briefer is fine—we will ask the right follow-ups.

  2. 02

    Targeted shortlist

    We share senior profiles vetted against your scenarios—usually within 5–10 business days. Each comes with a real-work signal, not just a CV.

  3. 03

    Your interview, your bar

    Interview at your pace and against your own rubric. We coordinate logistics; you keep the hiring decision.

  4. 04

    Embed and ship

    Selected engineers join your rituals—standups, PRs, on-call where needed. We stay accountable for delivery and fit.

Need a specific shape we have not described? Tell us the role and the timeline—we will tell you honestly whether we are the right partner for it.

Talk to us about a hire