AI Engineer

About the company: United Tech is a global IT product company shaping the future of real-time social connection. With millions of users across North America, Europe, LATAM, and MENA, we build next-gen mobile and web apps for live-streaming and social networking. Our platforms enable connection at scale fast, interactive, and deeply engaging. The market is projected to exceed $206B by 2030, and we are already leading the evolution. Founded in Ukraine, scaling worldwide

About your role: We’re looking for an AI Engineer who wants to build production-grade AI systems, not just experiment with demos. This is a high-ownership, greenfield role where you’ll help build our AI platform from scratch, working directly with the Head of AI.  You’ll own initiatives end-to-end — from discovery and architecture decisions to production delivery — and play a key role in shaping how AI is used across the company.

You’ll work with a modern AI stack including Claude/OpenAI/Bedrock, RAG pipelines, eval frameworks (Promptfoo, Ragas, LangSmith), and agentic patterns. This role is ideal for someone who enjoys autonomy, strong engineering ownership, and proactively identifying the next highest-leverage opportunity to drive into production.

In this role, you will

• Design and build RAG and automation workflows inside our VPC environment.

• Create integrations across engineering, communication, and knowledge-management systems (Jira, Confluence, Slack, Google Drive, Git).

• Develop AI-powered pipelines for code quality checks, ticket auto-classification, documentation updates, release notes, and meeting summaries.

• Work on prompt engineering, model selection and routing (Haiku / Sonnet / Opus), and workflow optimization.

• Build evaluation and regression frameworks for AI workflows to prevent model-upgrade regressions.

• Create lightweight dashboards for engineering leads to surface delivery patterns and bottlenecks.

• Own initiatives end-to-end: scope → design → ship → measure → iterate.

It’s all about you

• 5+ years of production experience with Python (services, async, API integrations, clean and testable code).

• Hands-on experience with LLM APIs in production: Anthropic Claude (Opus/Sonnet/Haiku), OpenAI, AWS Bedrock.

• Strong understanding of RAG systems: chunking, embeddings, hybrid search, re-ranking, grounding/citations.

• Prompt engineering + structured outputs + tool/function calling.

• Experience with eval/regression frameworks: Promptfoo, Ragas, LangSmith, or custom evaluation harnesses.

• Agentic patterns: ReAct, function-calling loops, fallbacks.

• Vector databases: pgvector, Pinecone.

• Workflow orchestration: n8n, Airflow, or custom orchestration systems.

• Observability: token-spend tracing, latency monitoring, model routing.

• Solid AWS fundamentals: IAM, Lambda, S3, CloudTrail — comfortable deploying inside VPC environments independently.

• CI/CD + pipeline hooks (GitLab/GitHub), webhooks, event-driven architectures.

• Basic SQL skills for analytical queries and metrics dashboards.

• Driver mindset: proactively identifies the highest-leverage opportunity and drives it to production

• B2 English level


Would be a plus

• Real REST integrations with 2–3+ APIs

• Experience with workflow orchestration tools.

• Prompt evaluation tooling such as  LangSmith is nice to have

• Experience with Docker

• RAG experience: embeddings and vector stores (pgvector, Pinecone, or similar) for knowledge base use cases

What we offer

Hiring process

• Intro call

• Technical Interview

• Final Interview

• Reference check

• Offer