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.