GenAI Sr. Developer and Lead

GenAI Sr. Developer and Lead

About the role

As a Senior Generative AI Developer and Lead, you will make an impact by designing, developing, and delivering enterprise-grade Generative AI solutions that enable business transformation through intelligent automation and AI-powered experiences. You will be a valued member of the AI Engineering team and work collaboratively with solution architects, data engineers, security teams, platform engineers, stakeholders, and global delivery teams to build scalable and secure AI applications.

* Please note that this position is not eligible for visa transfer or sponsorship now or at any time in the future
* In this role, you will:

* Design, develop, and deploy production-ready Generative AI applications on AWS using Amazon Bedrock, Python, serverless technologies, and modern cloud-native architectures.

* Build AI agents and agentic workflows leveraging Lang Chain, Lang Graph, Retrieval-Augmented Generation (RAG), and enterprise knowledge repositories to deliver intelligent business solutions.

* Act as the primary technical liaison for clients, leading architecture discussions, solution demonstrations, security reviews, and technical workshops with customer stakeholders.

* Provide technical leadership to distributed engineering teams through design reviews, code reviews, mentoring, and knowledge-sharing sessions to ensure high-quality delivery.

* Implement robust LLM evaluation frameworks, responsible AI controls, guardrails, observability practices, and monitoring strategies to ensure reliable and safe AI solutions.

* Collaborate across infrastructure, security, platform engineering, and data teams to remove dependencies, mitigate delivery risks, and drive successful project outcomes.

* Track program milestones, communicate progress effectively to stakeholders, manage escalations, and ensure timely delivery of key initiatives.

Work model

We believe hybrid work is the way forward as we strive to provide flexibility wherever possible. Based on this role's business requirements, this is a hybrid position requiring associates to work from a client or Cognizant office in Jersey City, New Jersey. Regardless of your working arrangement, we are here to support a healthy work-life balance through our various wellbeing programs.

The working arrangements for this role are accurate as of the date of posting. This may change based on the project you're engaged in, as well as business and client requirements. Rest assured; we will always be clear about role expectations.

What you need to have to be considered

* 10+ years of software development experience, including at least 3 years building AI/ML or Generative AI solutions in enterprise environments.

* Strong Python development expertise with proven experience developing, deploying, and supporting production-grade LLM-powered applications.

* Hands-on experience with AWS services including Amazon Bedrock, Lambda, ECS/Fargate, Step Functions, Event Bridge, IAM, S3, and containerized solutions using Docker.

* Deep experience building agentic AI solutions using Lang Chain, Lang Graph, Retrieval-Augmented Generation (RAG), and vector database technologies.

* Strong understanding of prompt engineering, LLM evaluation methodologies, responsible AI practices, guardrails, and model performance optimization.

* Experience developing RESTful APIs and microservices using FastAPI or similar frameworks.

* Working knowledge of cloud security, IAM policies, data privacy, encryption practices, and handling sensitive data within AI-powered applications.

* Excellent communication and stakeholder management skills with the ability to present technical solutions to architects, security teams, and executive leadership.

These will help you stand out

* Experience implementing observability and tracing solutions for AI applications using Cloud Watch, Lang Smith, Open Telemetry, or similar platforms.

* Hands-on experience with PostgreSQL, DynamoDB, and data architectures supporting AI and machine learning workloads.

* Knowledge of cost optimization strategies for LLM applications, including token management, caching, and model selection approaches.

* Experience with…