This role has closed. Capco has taken the posting down.
hirly last saw it live on 7 September 2026. See similar open roles below, or browse all jobs in Pune.
Capco
AI Engineer
India - Bengaluru; India - Pune
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hirly's read of this role
- Seniority
- Mid level
- Country
- IN
- Work mode
- On-site / unstated
- First seen by hirly
- 7 Sept 2026
Derived automatically from the posting.
the posting
Job Title: GenAI Developer/ Engineer
About Us
“Capco, a Wipro company, is a global technology and management consulting firm. Awarded with Consultancy of the year in the British Bank Award and has been ranked Top 100 Best Companies for Women in India 2022 by Avtar & Seramount . With our presence across 32 cities across globe, we support 100+ clients across banking, financial and Energy sectors. We are recognized for our deep transformation execution and delivery.
WHY JOIN CAPCO?
You will work on engaging projects with the largest international and local banks, insurance companies, payment service providers and other key players in the industry. The projects that will transform the financial services industry.
MAKE AN IMPACT
Innovative thinking, delivery excellence and thought leadership to help our clients transform their business. Together with our clients and industry partners, we deliver disruptive work that is changing energy and financial services.
#BEYOURSELFATWORK
Capco has a tolerant, open culture that values diversity, inclusivity, and creativity.
CAREER ADVANCEMENT
With no forced hierarchy at Capco, everyone has the opportunity to grow as we grow, taking their career into their own hands.
DIVERSITY & INCLUSION
We believe that diversity of people and perspective gives us a competitive advantage.
Location - Bangalore
Experience - 6 to 10
Skills and Qualifications :
Preferred skills:
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
Work with front-end technologies (e.g., React, Angular, Vue.js, JavaScript, TypeScript, HTML, CSS) and back-end frameworks (e.g., Python with Flask/Django/FastAPI, Node.js, Go)
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.