Agentic AI Data Engineer
About The Position
EXL (NASDAQ: EXLS) is a leading data analytics and digital operations and solutions company. We partner with clients using a data and AI-led approach to reinvent business models, drive better business outcomes and unlock growth with speed. EXL harnesses the power of data, analytics, AI, and deep industry knowledge to transform operations for the world’s leading corporations in industries including insurance, healthcare, banking and financial services, media and retail, among others. EXL was founded in 1999 with the core values of innovation, collaboration, excellence, integrity and respect. We are headquartered in New York and have more than 54,000 employees spanning six continents. For more information, visit www.exlservice.com. EXL never requires or asks for fees/payments or credit card or bank details during any phase of the recruitment or hiring process and has not authorized any agencies or partners to collect any fee or payment from prospective candidates. EXL will only extend a job offer after a candidate has gone through a formal interview process with members of EXL’s Human Resources team, as well as our hiring managers. EXL is the indispensable partner for leading businesses in data-led industries such as insurance, banking and financial services, healthcare, retail and logistics. We bring a unique combination of data, advanced analytics, digital technology and industry expertise to help our clients turn data into insights, streamline operations, improve customer experience, and transform their business. Our partnerships with clients are built on a foundation of collaboration – and we’ve been chosen as a partner by nine of the top ten leading US insurance companies, nine of the top 20 global banks, and six of the top ten US health care payers. We function as one team to make your goals our goals, whether that’s unlocking the value of generative AI or embedding analytics into workflows that reduce risk or power your growth. Clients choose EXL as their transformation partner for many reasons. Our geographic diversity make talent all over the world instantly accessible. Digital accelerators enable unmatched speed-to-value, letting you realize results fast. It’s our people that truly set us apart, though, including the 1,500 data scientists we have dedicated to our generative AI practice. And our more than twenty years of experience in delivering business services, garnering stellar client references, and maintaining a solid balance sheet are reassuring to our C-suite clients. Find out for yourself why clients, employees, and analysts think we’re some of the best in the business. Contact us to see how we can help you achieve your goals.
Requirements
- Strong experience with AWS services, including: Amazon S3, Glue, Lambda, Step Functions, Amazon Redshift / Athena, Amazon SageMaker (training, deployment, pipelines), Amazon Bedrock (foundation models, agents, knowledge bases)
- Experience with LLMs and generative AI systems
- Hands-on with agent frameworks (e.g., multi-agent orchestration, tool calling, planning systems)
- Familiarity with AgentCore / agent orchestration platforms
- Understanding of RAG architectures, embeddings, and vector databases
- Experience with model deployment, inference optimization, and prompt engineering
- Strong proficiency in Python and SQL
- Experience with ETL/ELT tools and frameworks
- Distributed data processing (Spark, PySpark, or similar)
- Streaming technologies (Kafka, Kinesis, or similar)
- Data modeling and schema design
- Experience with vector databases (e.g., Pinecone, FAISS, OpenSearch)
- Knowledge of data lakehouse architectures (Delta Lake, Iceberg, Hudi)
- Containerization (Docker) and orchestration (Kubernetes)
- CI/CD for ML and data pipelines
Responsibilities
- Design and implement agentic AI systems that autonomously orchestrate data workflows and decision pipelines
- Build scalable data pipelines for structured and unstructured data (batch + real-time)
- Develop and manage LLM-powered applications using retrieval-augmented generation (RAG), tool use, and multi-agent frameworks
- Integrate AWS AI/ML services into production-grade architectures
- Develop and optimize data lakes, warehouses, and lakehouse architectures
- Build APIs and microservices to expose AI/ML capabilities
- Ensure data quality, governance, and security across pipelines
- Collaborate with data scientists, ML engineers, and product teams to deploy AI solutions
- Implement monitoring, logging, and observability for AI agents and pipelines
- Optimize cost and performance of cloud-based AI workloads
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
