Senior AI/ML Engineer

Fidelity•Westlake, TX

About The Position

Fidelity is seeking a hands-on Senior Engineer working at the intersection of data engineering and AI/ML/LLM engineering. The role spans the end-to-end lifecycle, from building robust data pipelines that feed AI systems to deploying and operating AI, LLM, and retrieval systems at scale. This is an engineering role, not a data science role, focused on production-grade Python, AWS and Snowflake data and deployment patterns, CI/CD, and the operational reliability of AI-powered systems. The engineer will contribute to Fidelity's advanced analytics/insights team, which owns data engineering, advanced analytics/insights, and production AI/ML/LLM engineering for HR technologies. The team builds real-time and batch data infrastructure on AWS and Snowflake, analytics platforms, and the engineering foundation needed to operate production AI systems. Fidelity will not provide immigration sponsorship for this position. Fidelity is transitioning to a full-time onsite working model through a phased rollout across regions and roles; current onsite requirements vary by role and location and may evolve. This transition does not apply to fully remote roles. Fidelity's business is subject to financial-industry laws and regulations that may restrict hiring or association with individuals with certain criminal histories.

Requirements

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, including EC2, S3, Lambda, Step Functions, SageMaker, IAM, and RDS.
Experience building and operating data pipelines using Spark, Airflow, or streaming frameworks such as Kafka or Kinesis.
Experience deploying and monitoring AI/ML/LLM services in containerized environments such as Docker and Kubernetes.
Experience with CI/CD and Infrastructure as Code tools such as Terraform, CloudFormation, or similar.
Comfort debugging complex distributed systems using evidence-driven approaches.
Experience with vector databases and retrieval-augmented generation (RAG) patterns.
Familiarity with LLM frameworks such as LangChain, LlamaIndex, or similar, and agent orchestration.
Experience with observability tooling such as Datadog or CloudWatch.
Familiarity with event-driven architectures and real-time streaming systems.
Ability to work hands-on and raise technical standards through engineering execution.

Nice To Haves

Experience designing developer-facing APIs, SDKs, or CLI tools.
Understanding of agentic AI patterns and multi-step reasoning workflows.

Responsibilities

Design and build real-time and batch data pipelines for ingestion, transformation, streaming, and delivery into analytics and AI/ML systems.
Build resilient data connectors, chunking and embedding workflows, and parallel processing frameworks with data integrity guarantees.
Optimize ETL/ELT workflows in AWS and Snowflake, including indexing, partitioning, and 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, including retrieval quality metrics, latency tracking, drift detection, and alerting.
Translate prototypes into pragmatic, hardware-efficient, production-grade systems that are simple to operate.
Evaluate open-source AI/ML frameworks and adopt production-ready solutions or replace unnecessary complexity with maintainable implementations.
Develop production-grade Python code with rigorous testing, clean interfaces, and maintainability practices.
Work within Git-based workflows and CI/CD pipelines to support reliable promotion across development, UAT, and production environments.
Contribute to operational readiness through runbooks, incident response, and production support.
Raise technical standards through direct execution and engineering excellence.
Debug complex distributed systems using evidence-driven approaches.