Role overview
Senior AI Engineer (Full-Stack) — Detailed Job Description
Position: Senior AI Engineer (Full-Stack)
Location: Remote (10 Hours/ Day)
Experience Required: 5+ years Python engineering, 3+ years multi-agent systems
Type: Contract
ROLE SUMMARY
We are seeking a highly experienced Senior AI Engineer to lead the development of
production-grade multi-agent AI systems, backend services, LLM orchestration, and full-stack. AI-driven product experiences. The ideal candidate possesses deep technical expertise across. Python backends, multi-agent workflows, LLM integrations, RAG pipelines, multimodal processing, and frontend engineering.
What you'll work on
● Design and implement scalable multi-agent architectures: supervisor patterns,
orchestrators, shared memory/state, workflow dependencies, checkpointing, retries,
and debuggability.
● Build agent-driven coding workflows with hooks, background tasks, and toolchains
integrating AI coding tools.
● Develop high-performance Python backend services using FastAPI, async
concurrency, typed schemas, and secure API gateways.
● Build distributed task processing pipelines with Celery + Redis (or equivalents) for
long-running AI workloads.
● Integrate multiple LLM providers with routing, fallback logic, streaming, cost
optimization, tool/function calling, and JSON-structured output handling.
● Build evaluation pipelines for LLM-as-judge, human-in-loop reviews, automated prompt
regression tests, and iterative prompt optimization workflows.
● Develop agentic search and crawling workflows using
Playwright/Selenium/Firecrawl with LLM-ready content extraction and error
handling.
● Implement production-grade RAG pipelines: vector DBs, hybrid search,
chunking, metadata/RBAC tagging, embedding optimization, and retrieval
policy design.
● Build real-time streaming infrastructure using SSE/WebSockets, Redis caching
layers, pre-computation and rate-limiting strategies.
● Work on PostgreSQL schema design, DynamoDB key-value workflows, and ClickHouse
analytics setups for event and BI use cases.
● Implement multimodal AI features: Whisper STT, TTS, OCR, vision models, document
parsing, and image generation workflows.
● Support full-stack development in React/Next.js, TypeScript, Tailwind, real-time chat
interfaces, and browser extension workflows.
● Establish DevOps best practices using Docker, CI/CD pipelines, monitoring
dashboards, and containerized deployments.
MUST-HAVE SKILLS
● 5+ years Python (async, concurrency, FastAPI, Pydantic).
● 3+ years multi-agent workflow development (LangGraph or equivalent).
● Strong expertise in Celery + Redis or equivalent distributed compute frameworks.● Multi-LLM integration experience across OpenAI, Anthropic, Google, xAI.
● Proven RAG, vector search, embedding pipelines, and retrieval implementation experience.
● Strong background in web crawling/automation using Playwright/Selenium.
● Experience in building streaming endpoints and caching layers.
● Solid data engineering experience with Postgres, DynamoDB, and ClickHouse.
● Frontend engineering in React/Next.js + TypeScript.
NICE-TO-HAVE SKILLS
● Experience with Whisper, ElevenLabs, multimodal vision systems.
● Experience with GEPA-style prompt optimization loops.
● Experience with browser extension development for AI product workflows.
● Kubernetes familiarity and advanced MLOps methodologies.
SUCCESS METRICS
● High reliability multi-agent workflows with automated recoverability.
● Efficient and deterministic RAG retrieval systems.
● Low-latency streaming architecture supporting real-time AI UI.
● Successful multi-LLM orchestration with cost reduction and fallback stability.
● Production-ready evaluation and regression testing frameworks.
SUBMISSION REQUIREMENTS
● CVs with highlighted relevant project work.
● Examples or case studies of multi-agent systems built.
● Details on LLM integration experience
Job Type: Contract
Pay: From $1,106.00 per month
Work Location: Remote