About the Role:-
As a Forward Deployed Engineer, you will work directly with customers to understand their hardest problems, then design, build, and deploy GenAI and agentic AI solutions in their environment. You sit at the intersection of engineering and customer success: part solutions architect, part builder, and part product advocate. You will spend significant time on client sites or in client-facing workshops, and you will bring real customer feedback back to the product and engineering teams.
Key Responsibilities:-
- Embed with customer teams to scope use cases, map workflows, and identify where LLM and agentic AI solutions will deliver measurable business value.
- Rapidly prototype and ship production-grade LLM applications, including RAG systems, multi-step agents, and tool-integrated workflows, often within weeks rather than months.
- Integrate AI solutions with customer systems such as CRMs, ERPs, data warehouses, ticketing platforms, and internal APIs.
- Write clean, maintainable Python code for data pipelines, API services, and agent orchestration, and own deployments end to end.
- Design evaluation frameworks and success metrics with customers, and continuously measure accuracy, latency, cost, and hallucination rates in production.
- Translate ambiguous business requirements into technical specifications, architecture diagrams, and implementation plans.
- Lead technical workshops, demos, and training sessions for customer stakeholders, from engineers to executives.
- Handle security, compliance, and data governance requirements within each customers environment, including data residency and access controls.
- Serve as the voice of the customer internally, feeding product gaps, feature requests, and recurring patterns back to the core product team.
- Document reusable patterns, reference architectures, and playbooks that accelerate future deployments.
Required Skills and Qualifications:-
- Bachelors or Masters degree in Computer Science, Engineering, or a related field.
- 3+ years of software engineering experience, with strong proficiency in
Python
and experience building and deploying backend services (FastAPI, Flask, or similar). - Hands-on experience building
LLM-based applications
using APIs from providers such as OpenAI, Anthropic, Azure OpenAI, or Hugging Face. - Practical experience with
Agentic AI
systems, including tool/function calling, multi-step reasoning, and frameworks such as LangChain, LangGraph, or CrewAI. - Working knowledge of RAG pipelines, embeddings, and vector databases (FAISS, Pinecone, Weaviate, Chroma, or pgvector).
- Comfort with ambiguity and a bias toward action: you can scope a problem, make reasonable assumptions, and deliver a working solution quickly.
- Excellent communication skills, with the ability to explain technical trade-offs to non-technical stakeholders and earn trust in client meetings.
- Willingness to travel within India and occasionally internationally for client engagements.
Interested candidate can directly share your resumes to vijayravi.r@prodapt.com with the below details.
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