Generative AI Engineer

Capco; Bengaluru; On-site; INR 2,000,000 - 3,200,000; Full time

Job summary

Capco in Bengaluru is seeking an experienced AI/ML engineer to build scalable GenAI-driven applications. The role emphasizes Python mastery, RESTful services, and modern AI frameworks to deliver business-focused solutions.

You will work with LangChain, Snowflake Cortex, and multimodal models, collaborating with data scientists and engineers to deploy robust, scalable AI systems in a cloud environment.

Qualifications

• Proficient in Python with advanced async programming and OOP.
• Hands-on experience with GenAI frameworks and large language models.
• Strong backing in RESTful API design and microservices.
• Experience with SQL and NoSQL databases and schema optimization.

Responsibilities

• Develop scalable Python applications focused on GenAI.
• Work with Snowflake Cortex and other AI frameworks as a plus.
• Apply document chunking and embeddings techniques.
• Design and optimize schemas for PostgreSQL, MySQL, and NoSQL stores.
• Build apps around foundation models for business needs.
• Experiment with Retrieval-Augmented Generation and prompt engineering.
• Lead intelligent autonomous agents and multi-agent systems.
• Leverage LangChain, AutoGen, Semantic Kernel, and Crew AI.
• Develop MCP solutions to standardize data access for AI apps.
• Create full-stack apps integrating AI models and agentic systems.
• Design RESTful APIs and microservices; deploy on AWS/Azure/GCP.
• Implement MLOps/DevOps for CI/CD, monitoring, and lifecycle management.

Skills

Advanced Python

GenAI frameworks

REST APIs

SQL NoSQL DBs

Cloud platforms

Tools

LangChain

LlamaIndex

Haystack

Semantic Kernel

Snowflake Cortex

TensorFlow

PyTorch

PostgreSQL

MongoDB

Cassandra

AutoGen

Crew AI

Job description

Programming: Advanced Python (async programming, OOP, REST APIs, FastAPI, Flask, Pandas, NumPy)

GenAI Frameworks: LangChain, LlamaIndex, Haystack, Semantic Kernel

Machine Learning and AI: Snowflake Cortex, TensorFlow, PyTorch

Key Responsibilities:

• Develop scalable Python applications focused on GenAI
• Knowledge of Snowflake Cortex is a big plus.
• Learn and apply techniques like document chunking and embeddings
• Proficient in both SQL (e.g., PostgreSQL, MySQL) and NoSQL (e.g., MongoDB, Cassandra) databases, including schema design and optimization.
• Design, develop, and fine-tune applications built around foundation models (e.g., LLMs, multimodal models) for specific business needs
• Implement and experiment with generative AI techniques, including but not limited to Retrieval-Augmented Generation (RAG) and prompt engineering
• Lead the implementation of intelligent autonomous agents and multi-agent systems capable of complex decision-making, task execution, and interaction with external systems
• Utilize and contribute to agentic AI frameworks (e.g., LangChain, AutoGen, Semantic Kernel, Crew AI) to build robust and scalable AI agents
• Develop and integrate Model Context Protocol (MCP) solutions to standardize how AI applications access and utilize external data sources, tools, and real-time information
• Lead the development of full-stack applications that integrate generative AI models and agentic systems, ensuring seamless user experiences
• Design and implement scalable RESTful APIs and microservices to expose AI functionalities
• Deploy, manage, and optimize AI/ML workloads and full-stack applications on at least one major cloud platform (AWS, Azure, or GCP)
• Implement LLMOps/MLOps and DevOps best practices for continuous integration, continuous delivery (CI/CD), model deployment, monitoring, and lifecycle management
• Follow coding best practices and contribute to testing and documentation
• Stay abreast of the latest advancements in generative AI, agentic systems, foundation models, and related fields through continuous research and experimentation
• Collaborate effectively with cross-functional teams, including product managers, data scientists, researchers, and other engineers
• Communicate effectively with both technical and non-technical team members, ensuring alignment and understanding across all project phases.