Senior Technical Lead - Agentic AI
First seen by Alion on Aug 29, 2026.
About the Role :
We're looking for a Senior Technical Lead to own the architecture and delivery of our Agentic AI / Generative AI initiatives from early prototyping through production deployment at scale. This is a hands-on leadership role: you'll design and build LLM-powered agent systems yourself while also setting technical direction and mentoring a small team of AI/ML engineers. You'll work closely with product, data, and platform teams to turn GenAI capability into real, reliable, production-grade systems not just demos.
What You'll Do :
- Architect and lead development of agentic AI systems multi-step reasoning agents, tool-use/function-calling pipelines, and orchestration frameworks (e.g., LangGraph, AutoGen, CrewAI, or custom agent orchestration).
- Design and productionize Retrieval-Augmented Generation (RAG) pipelines, including chunking strategy, embeddings, vector search, and hybrid retrieval.
- Lead evaluation and selection of foundation models (proprietary and open-source) and drive prompt engineering, fine-tuning, and model-routing strategy across use cases.
- Own technical architecture decisions for scalability, latency, cost, and reliability of LLM-based systems in production.
- Set and enforce engineering standards for testing, evaluation (offline/online), guardrails, hallucination mitigation, and observability of agentic systems.
- Lead, mentor, and grow a team of AI/ML/backend engineers run technical design reviews, code reviews, and career development.
- Partner with Product, Data Science, Security, and Compliance to ensure GenAI systems meet privacy, security, and responsible-AI requirements.
- Stay current with the fast-moving GenAI/agentic landscape and translate relevant advances into the team's roadmap.
- Represent the AI engineering function in cross-functional and executive-level discussions on GenAI strategy and roadmap.
What We're Looking For :
- 10+ years of overall software engineering experience, including 4+ years working directly with ML/AI systems and 2+ years specifically building and shipping LLM-based or agentic AI applications in production.
- Deep hands-on experience with LLM application development: prompt engineering, RAG architectures, vector databases (e.g., Pinecone, Weaviate, Milvus, pgvector), and embeddings.
- Practical experience building multi-agent or tool-using AI systems (agent orchestration frameworks, function/tool calling, memory management, planning/reasoning loops).
- Strong software engineering fundamentals Python required; experience designing scalable, distributed, production systems (APIs, microservices, cloud-native architecture).
- Experience with at least one major cloud platform (AWS, Azure, or GCP) and MLOps/LLMOps tooling (e.g., MLflow, LangSmith, Weights & Biases, or equivalent).
- Working knowledge of fine-tuning and evaluation techniques for LLMs (e.g., LoRA/PEFT, RLHF concepts, offline/online eval frameworks).
- Demonstrated experience leading or mentoring engineers technical leadership, design ownership, and cross-team collaboration, even without formal people-management title.
- Strong communication skills able to translate between deep technical detail and business/executive stakeholders.
Nice to Have :
- Experience with open-source LLM deployment and fine-tuning (Llama, Mistral, etc.) alongside proprietary APIs (OpenAI, Anthropic, Gemini).
- Contributions to GenAI/agentic open-source projects, technical publications, or conference talks.
- Experience building AI systems in a regulated industry (finance, healthcare, telecom) with attention to compliance, privacy, and responsible-AI practices.
- Experience with model guardrails, red-teaming, or AI safety/evaluation frameworks.
- Prior experience formally managing a team of engineers (not just technical leadership).
Why This Role :
You'll be one of the senior-most technical voices shaping how the company builds and ships agentic AI with real ownership over architecture decisions, a growing team to lead, and direct visibility into company strategy around GenAI investment.
About the company :
EazyML, recognized by Gartner, EazyML specializes in Responsible AI. Our solutions facilitate proactive compliance and sustainable automation, and the company is associated with breakthrough startups like Amelia.ai.
Skills
Artificial Intelligence, Agentic AI, Generative AI, LangGraph, RAG, LLM, Machine Learning, MLOps, AWS, Python