Role : Principal AI/ML Architect

About Egen :

Egen is a fast-growing, entrepreneurial technology company with a data-first mindset. We bring together exceptional engineering talent and advanced technology platforms, including Google Cloud and Salesforce, to help clients drive action and impact through data and insights. We are committed to being a place where talented people choose to do their best work - applying deep engineering and technology expertise to envision how data, AI, and platforms can change the world for the better.

About the opportunity :

As a Principal AI/ML Architect, you will set the technical direction for Egen's most complex generative AI, agentic AI, and applied machine learning engagements while remaining personally hands-on in the work that matters most. You will own the hardest architectural problems in our portfolio : agentic platforms operating at scale, applied-ML solutions, advanced retrieval systems, and AI in regulated or high-stakes environments.

What you will do :

- Set enterprise AI architecture and technical direction : Own the end-to-end architecture for complex GenAI, agentic AI, and ML platforms.

- Build at the frontier - hands-on : Stay close to the code on the highest-leverage technical work, including foundation-model and embedding fine-tuning, advanced RAG, and novel agentic workflows.

- Engineer AI for production : Design for latency, reliability, security, cost, scalability, and maintainability.

- Architect agentic systems at scale : Design and operate multi-step reasoning and multi-agent workflows using ADK, LangChain, and MCP.

- Establish evaluation, observability, and responsible AI standards : Define measurable quality criteria and production telemetry.

- Shape data and retrieval architectures : Design production-scale retrieval and knowledge systems.

- Advise clients and shape opportunities : Partner with client executives to translate business strategy into AI roadmaps.

- Multiply engineering capability : Raise the technical bar through architecture reviews, design documents, and mentoring.

- Own outcomes across the full lifecycle : Guide initiatives from problem framing through production rollout.

Your technical toolkit :

- Languages : Expert-level Python, shell scripting, API and service design.

- Models and AI : Google Gemini, GPT-class models, LLaMA, fine-tuning, and evaluation.

- Agentic AI : Google ADK, LangChain, MCP, workflow orchestration, and state management.

- Retrieval and search : Advanced RAG, hybrid/semantic search, embeddings, and vector platforms (Vertex AI Vector Search, pgvector, Pinecone).

- Cloud : Google Cloud / Vertex AI, AWS, and Azure.

- MLOps/LLMOps : CI/CD, model/prompt versioning, observability, and drift detection.

Basic qualifications :

- Bachelor's or Master's degree in a technical field.

- 15+ years of progressive experience in software engineering, ML, data, or AI.

- Proven record of deploying generative AI, agentic AI, or applied-ML products into production.

- Strong client-facing experience with executive stakeholders.