Forward Deployed Engineer - Agentic & Gen AI

datavruti; Bengaluru; Hybrid; INR 1,800,000 - 3,000,000; Full time

Job summary

datavruti seeks an experienced Forward Deployed Engineer – Agentic AI & Generative AI to work with clients and internal teams to design, build, and deploy production-grade AI solutions.

The role requires hands-on Generative AI, LLMs, Python, RAG, APIs, and enterprise integrations, with rapid prototyping and productionization in a fast-paced, client-facing environment.

Qualifications

• 5-12 years of experience in software engineering, data science, AI/ML engineering, or related fields.
• Hands-on experience with Generative AI and LLM-based applications.
• Strong Python proficiency.
• Experience with AI agents and agent orchestration.
• REST APIs and enterprise system integration.

Responsibilities

• Translate business requirements into scalable AI/GenAI solutions.
• Design, develop, test, and deploy AI-powered applications and workflows.
• Build rapid POCs and production-ready solutions.
• Collaborate with client teams, Data Scientists, ML engineers, and architects.
• Troubleshoot production issues and optimize deployments.

Skills

Python

Generative AI

LLM-based applications

Agentic AI / AI Agents

REST APIs

Data Science

Education

Bachelor’s/Master’s in CS/IT/Data Science/AI

Tools

LangChain

LangGraph

LlamaIndex

Databricks

Snowflake

Job description

Hiring for: A US-based, AI-first data solutions company founded by seasoned technology leaders.

Role: Forward Deployed Engineer - Agentic & Gen AI

Positions: 1

Experience: 5 to 12 years

Type: On-site, Remote / Permanent

Salary: Up to INR 30 LPA

Notice Period: 15 days

About Role

We are looking for an experienced Forward Deployed Engineer – Agentic AI & Generative AI to work closely with clients, business stakeholders, and internal engineering teams to design, build, and deploy production-grade AI solutions.

The ideal candidate will have strong hands-on expertise in Generative AI, LLMs, Agentic AI, Python, RAG, APIs, and enterprise integrations, combined with strong software engineering and problem-solving skills. The candidate should be comfortable working in ambiguous environments, rapidly prototyping solutions, and taking them through to production.

Key Responsibilities

• Work directly with clients to understand business challenges, workflows, and technical requirements.
• Translate business requirements into scalable AI/GenAI solutions.
• Design, develop, test, and deploy AI-powered applications and workflows.
• Build rapid POCs and convert successful prototypes into production-ready solutions.
• Work closely with client engineering teams, Data Scientists, ML Engineers, and Solution Architects.
• Troubleshoot production issues and continuously optimize deployed solutions.
• Act as a technical bridge between clients and internal delivery/engineering teams.

Agentic AI & Generative AI

• Design and develop AI agents and agentic workflows capable of multi-step reasoning, planning, tool usage, and task execution.
• Develop solutions using LLMs such as Claude, OpenAI, Azure OpenAI, Gemini, or equivalent platforms.
• Build RAG (Retrieval-Augmented Generation) applications using enterprise data.
• Work with embeddings, vector databases, semantic search, and hybrid search.
• Implement prompt engineering, structured outputs, function/tool calling, context management, and memory.
• Develop AI-powered solutions for document processing, summarization, classification, information extraction, decision support, and workflow automation.
• Develop and implement multi-agent workflows where applicable.

AI Security & Governance

• Design secure enterprise AI solutions with appropriate RBAC, ACLs, and data access controls.
• Ensure that users can access only authorized information in RAG and agentic workflows.
• Implement retrieval filtering, secure context construction, audit logging, and data privacy controls.
• Evaluate AI applications for accuracy, relevance, hallucination, security, latency, and cost.
• Implement appropriate guardrails and responsible AI practices.

Engineering & Productionization

• Develop production-grade applications and APIs using Python and modern software engineering practices.
• Integrate AI solutions with enterprise applications, databases, APIs, and cloud platforms.
• Implement CI/CD, Git, testing, monitoring, and deployment practices.
• Optimize solutions for performance, scalability, reliability, and cost.
• Work with cloud platforms such as AWS, Azure, or GCP.
• Collaborate with Data Engineering and ML teams to productionize AI solutions.

Required Skills & Experience

• 5-12 years of experience in Software Engineering, Data Science, AI/ML Engineering, or related fields.
• Strong hands-on experience with Generative AI and LLM-based applications.
• Strong proficiency in Python.
• Hands-on experience with Agentic AI / AI Agents.
• Experience with RAG, embeddings, vector databases, and semantic search.
• Experience with LLM APIs such as Claude, OpenAI, Azure OpenAI, or Gemini.
• Strong understanding of REST APIs and enterprise system integration.
• Experience building and deploying production-grade applications.
• Strong understanding of AI evaluation, security, and governance.
• Excellent problem-solving and client-facing communication skills.

Preferred Skills

• Experience with LangGraph, LangChain, LlamaIndex, CrewAI, AutoGen, or similar frameworks.
• Hands-on experience with Claude / Anthropic APIs.
• Experience with Databricks, Snowflake, or modern data platforms.
• Experience with AWS, Azure, or GCP.
• Experience with Docker, Kubernetes, and CI/CD.
• Experience implementing AI guardrails and enterprise security.
• Knowledge of multi-agent architectures and agent orchestration.
• Experience working in consulting, solution engineering, or client-facing technical roles.
• Strong builder and ownership mindset.
• Ability to work effectively in ambiguous and fast-paced environments.
• Strong client and stakeholder management skills.
• Ability to quickly understand business problems and design practical solutions.
• Excellent communication and presentation skills.
• Strong systems thinking and technical problem-solving ability.
• Ability to balance business value, technical feasibility, security, scalability, and cost.

Education

Bachelor's or Master's degree in Computer Science, Information Technology, Data Science, Artificial Intelligence, Engineering, or a related discipline.