Lead consultant - Backend Engineer

Ready to shape the future of work
At Genpact, we don't just adapt to change-we drive it. AI and digital innovation are redefining industries, and we're leading the charge. Genpact's AI Gigafactory, our industry-first accelerator, is an example of how we're scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to agentic AI, our breakthrough solutions tackle companies most complex challenges.
If you thrive in a fast-moving, tech-driven environment, love solving real-world problems, and want to be part of a team that's shaping the future, this is your moment.
Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions - we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation, our teams implement data, technology, and AI to create tomorrow, today. Get to know us at genpact.com and on LinkedIn, X, YouTube, and Facebook.
Inviting applications for the role of Lead consultant - Backend Engineer
We are seeking a highly skilled Python GenAI Backend Engineer to join our team. In this role, you will design, develop, and maintain backend microservices and APIs that integrate with generative AI platforms, knowledge bases, and large language models. You will collaborate with cross-functional teams to deliver robust, scalable, and secure backend solutions that power next-generation AI-driven applications.
Responsibilities
.Design and implement RESTful and/or GraphQL APIs using Python frameworks (e.g., Django, Flask, FastAPI).
.Develop microservices and modular backend components for scalability and maintainability.
.Integrate third-party services, APIs, and internal systems.
.Work with message queues (RabbitMQ, Kafka) for asynchronous processing.
.Design, build, and maintain backend microservices and APIs in Python using frameworks such as Django or Flask
.Implement AI integration layers, including embedding generation, vectorization, vector search, and retrieval-augmented generation (RAG) pipelines
. Integrate with LLM and model-hosting platforms (e.g., AWS Bedrock) and implement prompt chaining and agent orchestration
. Build, test, and operate AI agent frameworks enabling multi-step, stateful workflows and task delegation
. Architect event-driven and serverless components to scale real-time inference and asynchronous jobs
. Ensure services are production-ready with automated CI/CD, Infrastructure-as-Code, logging, tracing, and alerting
. Collaborate with data scientists, ML engineers, and product owners to productionize models and implement guardrails
. Optimize for cost, latency, and throughput in model calls, embedding pipelines, and vector-index maintenance
. Produce clear API documentation, runbooks, and design documents participate in architectural reviews

Contributing to your BU/Practice by
.Delivering innovative, scalable backend solutions that drive GenAI-powered business value
.Enhancing the organization's AI integration capabilities and technical knowledge base
.Supporting the development of best practices and standards for GenAI backend engineering
.Collaborating effectively with cross-functional teams to achieve project and organizational goals

Qualifications we seek in you!
Minimum Qualifications
. Bachelor's degree in Computer Science, Engineering, or a related field
. Proven experience in backend development using Python
. Hands-on experience building APIs that call LLMs, generate embeddings, and perform vector searches
. Experience implementing RAG pipelines, knowledge-base connectors, and vectorization workflows
. Familiarity with LLM orchestration techniques such as prompt chaining and agent frameworks
. Experience integrating with cloud-based LLM/model platforms (e.g., AWS Bedrock)
. Strong engineering grounding in API design, authentication/authorization, and rate-limiting
. Experience with CI/CD, automated testing, and monitoring in production environments
Preferred Qualifications
.Master%27s degree in computer science, Engineering, or a related field
.Prior experience building AI-powered chatbots, virtual assistants, or automated agents in production
Strong proficiency in Python and frameworks like Django, Flask, or FastAPI.
.Experience with RESTful API design and development.
.Solid understanding of relational and NoSQL databases.
.Familiarity with containerization (Docker) and orchestration (Kubernetes).
.Knowledge of CI/CD tools (GitHub Actions, Jenkins, Azure DevOps).
.Understanding of cloud platforms (AWS, Azure, or GCP).

Why join Genpact
.Be a transformation leader - Work at the cutting edge of AI, automation, and digital innovation
.Make an impact - Drive change for global enterprises and solve business challenges that matter
.Accelerate your career - Get hands-on experience, mentorship, and continuous learning opportunities
.Work with the best - Join 140,000+ bold thinkers and problem-solvers who push boundaries every day
.Thrive in a values-driven culture - Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress
Come join the tech shapers and growth makers at Genpact and take your career in the only direction that matters: Up.
Let's build tomorrow together.Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation.
Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training.