Senior AI​/ML Engineer

Fidelity will not provide immigration sponsorship for this position.

Job Description:

The Role We are looking for a Senior Engineer who operates at the intersection of data and AI/ML/LLM Engineering. You will work on the end-to-end lifecycle from building robust data pipelines that feed AI systems, to deploying and operating AI/LLM and retrieval systems s is a hands-on engineering role, not data science.

Real-time and batch data pipeline engineering on AWS and Snowflake Production-grade Python, testing, and CI/CD discipline AWS and Snowflake-based data and deployment patterns

Product ionizing AI/ML/LLM systems (serving, agents, retrieval pipelines)
Observability, monitoring, and operational reliability of AI-powered systems

The Skills and Expertise You Bring Primarily hands-on, with the ability to raise technical standards through direct execution and engineering excellence.

Design and build real-time and batch data pipelines: ingestion, transformation, streaming, and delivery into analytics and AI/ML systems

Build resilient data connectors, chunking/embedding workflows, and parallel processing frameworks with data integrity guarantees

Optimize ETL/ELT workflows in AWS and Snowflake including indexing, partitioning and efficient resource utilization

Deploy, scale, and operate AI/ML/LLM services including model serving, agent orchestration, and retrieval pipelines

Implement monitoring and observability for production AI systems for retrieval quality metrics, latency tracking, drift detection, and alerting

Translate prototypes into production-grade systems that are pragmatic, hardware-efficient, and simple to operate

Evaluate open-source AI/ML frameworks critically; adopt what's production-ready, replace bloat with lean, maintainable implementations

Develop production-grade Python code with strong testing, clean interfaces, and maintainability practices

Work within Git-based workflows and CI/CD pipelines to support reliable promotion across dev, UAT, and production environments

Contribute to operational readiness through runbooks, incident response, and production support

Strong Python skills for production data and AI/ML systems, including rigorous testing and maintainable code Strong SQL skills and experience with Snowflake for analytics and data pipeline workloads

Experience with AWS services (EC2, S3, Lambda, Step Functions, Sage Maker, IAM, RDS)
Experience building and operating data pipelines using Spark, Airflow, or streaming frameworks (Kafka, Kinesis)
Experience deploying and monitoring AI/ML/LLM services in containerized environments (Docker, Kubernetes)

Experience with CI/CD and Infrastructure as Code (Terraform, Cloud Formation, or similar)
Comfort debugging complex distributed systems with evidence-driven approaches

Experience with vector databases and retrieval-augmented generation (RAG) patterns

Familiarity with LLM frameworks (Lang Chain, Llama Index, or similar) and agent orchestration

Experience with observability tooling such as Datadog or Cloud Watch Familiarity  with event-driven architectures and real-time streaming systems

Experience designing developer-facing APIs, SDKs, or CLI tools

Understanding of agentic AI patterns and multi-step reasoning workflows

The Team Our advanced analytics/insights team owns the data engineering, advanced analytics/insights, and production AI/ML/LLM Engineering for the HR technologies. Our work spans real-time and batch data infrastructure on AWS and Snowflake, analytics platforms, and the engineering backbone that makes AI/ML/LLM systems production-real. We are engineers who build with craft, ship with confidence, and take ownership of what runs.

Fidelity’s Onsite Working Model Fidelity is transitioning to a full-time onsite working model through a phased…