Zensar
AI Forward Deployed Engineer - Java & GenAI
Skills
1 month ago
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Important information
Contract type:
Permanent
Location:
Mumbai, Maharashtra, India
Work mode:
Hybrid
Published on:
18 September 2026
What they need
The AI Forward Deployed Engineer works at the intersection of AI, engineering, and business, partnering closely with stakeholders to identify use cases, build prototypes, and deliver production-grade AI solutions. This role requires hands-on experience with LLMs, cloud platforms, APIs, and enterprise system integration, along with strong problem-solving and communication skills.
Role & responsibilities
- Identify and define AI use cases with business stakeholders
- Design and develop AI/ML and GenAI-based solutions (LLMs, RAG, agents)
- Build and deploy production-ready applications, copilots, and automation tools
- Integrate solutions with enterprise systems, APIs, and databases
- Collaborate with cross-functional teams for scalability, security, and reliability
- Rapidly iterate prototypes based on feedback and performance metrics
- Monitor and optimize solutions for accuracy, latency, and cost
- Create technical documentation and deployment guides
- Advise stakeholders on AI capabilities, risks, and best practices
Primary Skills
- Python / JavaScript / TypeScript / Java
- Large Language Models (LLMs)
- Retrieval-Augmented Generation (RAG)
- Prompt Engineering & Agentic Workflows
- APIs & Microservices Development
- Cloud Platforms (Azure / AWS / GCP)
- System Design & Solution Architecture
Secondary Skills
- Vector Databases (Pinecone, FAISS, etc.)
- MLOps / CI-CD pipelines
- Frontend frameworks (React, Angular)
- Security & Compliance in AI systems
- Monitoring & Observability tools
- Domain knowledge (Retail, Healthcare, Finance, etc.)
Preferred candidate profile
- Bachelors degree in Computer Science / Engineering / Data Science or equivalent
- Strong programming skills (Python, JavaScript/TypeScript, Java)
- Experience with API-based development, cloud platforms (AWS/Azure/GCP), and databases
- Hands-on experience with AI/ML technologies (LLMs, RAG, embeddings, vector DBs)
- Strong problem-solving, debugging, and system design skills
- Ability to work with business stakeholders and translate requirements
- Comfortable in fast-paced, ambiguous, customer-facing environments
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