GEN AI Developer
Pune, Maharashtra, India
Zensar
Zensar is a global organization which conceptualizes, builds, and manages digital products through experience design, data engineering, and advanced analytics for over 200 leading companies. Our solutions leverage industry-leading platforms to...TP4 Developer
Key Responsibilities:
- Generative AI Systems Design: Architect scalable, high-performance applications powered by Generative AI models (e.g., LLMs, diffusion models), with a focus on real-world usability and business integration.
- Prompt Engineering & RAG Pipelines: Design and implement optimized prompt strategies and Retrieval-Augmented Generation (RAG) workflows using LangChain and similar frameworks.
- Agentic AI & Autonomous Workflows: Develop and manage intelligent agents capable of multi-step reasoning, planning, and decision-making using frameworks like LangChain Agents or custom implementations.
- Vector Store Integration: Design and integrate vector databases for semantic search and document retrieval in GenAI workflows.
- End-to-End AI Application Development: Build and deploy AI-driven applications from scratch using Python and modern ML/AI toolkits. Ensure clean integration with APIs, databases, and frontend services.
- Microservices & API Development: Create modular, maintainable backend services using microservices architecture. Ensure RESTful APIs for smooth communication.
- CI/CD & DevOps: Develop and maintain CI/CD pipelines for model and app deployment. Ensure reproducibility, automated testing, and smooth rollout using tools like GitHub Actions, GitLab CI/CD, or Jenkins.
- Database Management: Use PostgreSQL and NoSQL databases effectively in storing structured and unstructured data, with focus on performance, indexing, and scaling.
- Performance Optimization: Continuously monitor, benchmark, and optimize applications for performance, scalability, and cost-efficiency across cloud and on-prem environments.
- Collaboration & Mentorship: Work closely with product managers, AI researchers, and junior developers. Lead by example and provide technical mentorship in AI system design and production-readiness.
Required Qualifications:
- Technical Expertise:
- Strong proficiency in Python (mandatory) and experience with AI/ML libraries like FastAI, Hugging Face Transformers, and OpenAI APIs.
- Experience implementing LangChain workflows, prompt chaining, agents, tools, and memory systems.
- Hands-on experience building RAG systems using vector DBs like FAISS, Pinecone, Weaviate, or Chroma.
- Solid understanding of Generative AI technologies (LLMs, image/video generation, embeddings).
- Working knowledge of Agentic AI concepts for building autonomous tools and applications.
- Backend & Architecture:
- Strong skills in system design, API development, and microservices-based backend architecture.
- Experience with PostgreSQL and NoSQL databases (e.g., MongoDB, DynamoDB).
- Cloud & DevOps:
- Familiarity with CI/CD pipelines, containerization (Docker), and cloud deployments (AWS/GCP/Azure).
- Git-based version control and collaborative development workflows.
- Communication & Leadership:
- Ability to translate AI research into production-ready applications.
- Strong collaboration skills and experience leading engineering efforts or mentoring peers.
Preferred (Nice to Have):
- Experience working with LLMOps tools
- Exposure to data labeling, fine-tuning, or custom LLM training.
- Familiarity with streaming architectures or real-time AI inference.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: API Development APIs Architecture AWS Azure CI/CD DevOps Diffusion models Docker DynamoDB Engineering FAISS fastai GCP Generative AI Git GitHub GitLab Jenkins LangChain LLMOps LLMs Machine Learning Microservices MongoDB NoSQL OpenAI Pinecone Pipelines PostgreSQL Prompt engineering Python RAG Research Streaming Testing Transformers Unstructured data Weaviate
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