TechByte Talent Ltd
Artificial Intelligence Engineer
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Agentic AI Engineer
The Opportunity
We're working with a fast-moving organisation building production-grade agentic AI systems. Not prototypes, not proof-of-concepts, but reasoning agents that use tools, maintain state, retrieve knowledge, execute multi-step workflows, and know when to escalate to a human.
This is a rare chance to own the full lifecycle of agentic AI in production: architecture, orchestration, tool integration, evaluation, safety, observability, and cost optimisation across Azure OpenAI, Anthropic, open models, and provider-native agent SDKs.
What You'll Do
- Design and operate production agentic AI systems with robust tool-use, memory, and multi-step reasoning
- Select and integrate LLMs and agent frameworks (LangGraph, LangChain, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, or custom orchestration), balancing latency, cost, quality and compliance
- Engineer reliable tool-use patterns: function calling, structured outputs, MCP servers, permissions, retries, sandboxing, and audit trails
- Build retrieval and context-engineering pipelines: RAG, hybrid search, re-ranking, short/long-term memory, and context budgeting
- Own agent evaluation and safety: golden datasets, red-teaming, prompt-injection defences, PII controls, and production feedback loops
- Optimise for cost and performance: prompt caching, token budgeting, model routing, and batching
- Deploy agents as reliable services with CI/CD, canary releases, rollback plans, and provider failover
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What You'll Bring
- 4+ years in software, ML, or production AI engineering, with proven experience shipping reliable services (not just prototypes)
- 2+ years working hands-on with LLMs prompt/context engineering, structured outputs, function calling, RAG, evaluation, and production monitoring
- Strong Python skills: async programming, type hints, Pydantic-style validation, API design, and secure, maintainable service architecture
- Deep knowledge of agentic patterns: ReAct, plan-and-execute, reflection, state graphs, multi-agent orchestration, and human-in-the-loop design
- Experience with vector databases and retrieval systems (Pinecone, Weaviate, FAISS, Azure AI Search) and evaluation/observability tooling (LangSmith, Braintrust, Application Insights)
- Understanding of AI security and governance: prompt injection, data exfiltration, sandboxing, and compliance-ready audit trails
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Nice to have
- MCP server authoring
- Agent-to-Agent (A2A) protocols
- Multimodal agents
- Arabic/UAE localisation experience
- Regulated-industry AI governance
- Local inference (vLLM/TensorRT-LLM)
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
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