Role :

You will work as a Senior AI Consultant who embeds within a customer's business. Your job is to learn how the business makes money, find the highest-value problem, and build a working system that solves it.

You will not hand over a document and walk away. You will show working software early, own the roadmap, own the client relationship, and stay after go-live to run and improve the system.

Responsibilities :

1. Discovery :

- Learn how the customer makes money. Find the highest value problem to solve first.

2. The prototype :

- Build a working prototype fast, using real or sample data, to prove the idea.

3. Roadmap :

- Decide what to build and in what order, and set clear success measures tied to business outcomes.

4. The build :

- Design and ship the production system with the Hyderabad engineering team. This includes data integration, agents, retrieval, and evaluations.

5. The client relationship :

- Be the trusted technical contact for the customer, from engineers to senior leaders.

6. Go live and after :

- Deploy the system, watch how it performs, fix problems, and improve it over time.

7. Feedback on the product :

- Share what you learn in the field so our platform and internal tools get better.

Requirements :

- 1. Around 7 or more years of software engineering experience, including customer-facing or client delivery work.

- 2. Experience working at a consulting or professional services firm in a client-facing delivery role.

- 3. Full-stack development experience with strength in backend technologies. Strong programming skills in Python. Working knowledge of TypeScript or JavaScript.

- 4. Production experience with large language models, including prompt engineering and agent development.

- 5. You build with AI coding tools like Claude Code as your default way of working. You have built real apps and agents this way, not just used it for document generation or review.

- 6. Experience building retrieval-augmented generation (RAG) systems : chunking, embeddings, vector databases, retrieval, and reranking.

- 7. Experience building and deploying AI systems.

- 8. Experience integrating with APIs and enterprise systems.

- 9. Experience with at least one cloud platform (AWS, Azure, or GCP).

- 10. Experience building evaluations to measure accuracy, safety, latency, and cost.

- 11. Clear communication. You can explain a technical choice to an engineer and to a business leader.

- 12. High ownership and comfort with ambiguity. You can take an unclear problem and turn it into a plan.

- 13. Willingness to work onsite at client locations in India for extended periods and to travel as the work needs.

Nice to have :

- 1. Experience deploying AI systems in regulated industries such as insurance, banking, or the public sector.

- 2. Experience with on-premises or private cloud (VPC) deployments.

- 3. Experience with observability and tracing tools such as LangSmith or Braintrust.

- 4. Experience with data engineering and pipelines.

- 5. A history of side projects, open-source contributions, or products you shipped end-to-end.

- 6. Experience in embedded or forward-deployed roles before.

Stack and tools :

- Python, TypeScript, Claude, frontier and open-source models, RAG, agents, prompt engineering, evaluations, vector databases, retrieval pipelines, AWS, Azure, GCP, public/private cloud, REST APIs, and enterprise system connectors.