Principal Python Backend Engineer

Note: Fidelity is not providing immigration sponsorship for this position.   Principal Python Backend Engineer Bring a builder's mindset to Fidelity's Enterprise AI/ML Platform and help us scale the next generation of high-performance, production-grade backend systems. You will work on the core platform that connects tools, agents, data, and models—designing clean service abstractions, building resilient processing pipelines, shipping developer-friendly APIs and SDKs, and turning rapid prototypes into well-engineered, maintainable Python systems.

We hire exceptional, driven Python engineers first—people who take pride in clean code, fast learning, and high ownership. Deep knowledge of AI/ML is not a prerequisite; the domain knowledge and context can be learned on the job. What cannot be taught is the engineering rigour, the drive, and the instinct for simplicity that we look for. What you’ll do Build the core AI/ML services running in Kubernetes and locally in 'Playground' mode Design clean abstractions over vector databases and multistep Search/Information Retrieval pipelines Own automated real-time data ingestion for RAG: connectors, streaming pipelines, chunking/embedding strategies, parallel processing, retrieval metrics, resilience & restartability while guaranteeing ACID integrity of processed data and elimination of redundant document processing. Ship developer-friendly APIs/SDKs, CLIs, and templates that make it trivial to develop agents, tools, and information retrieval pipelines at enterprise scale. Instrument everything: distributed tracing for services & agentic/tool sessions, retrieval quality metrics, performance metrics, resource usage and failure forensics. Turn rapid prototypes into resilient systems—pragmatic designs that are simple to use, which scale in hardware efficient manner, and above all as simple as possible. Read and distill open-source frameworks, keep what’s valuable, replace the bloated with lean, well engineered Python modules.

Culture: Lead through code, productivity and knowledge sharing. Ask sharp questions, challenge complexity, and encourage others to do the same. We embrace a flat hierarchy where the best ideas win, regardless of seniority. What you bring Engineering perspective: 7+ years of professional software engineering experience, with the majority spent building and operating production-grade Python backend systems. This is not an entry-level role and we expect a track record of owning complex systems end to end. Strong Python service engineering: sound OOP, clear interfaces, thorough tests, and an obsession with readability and maintainability. Real-world performance tuning across services and data stores: concurrency, async I/O, queues, caching, SQL/NoSQL indexing, pagination, and backpressure. Experience building event-driven systems and/or real-time pipelines for ingestion and inference. Mastery of debugging complex, distributed behavior—reproducible experiments, simulations, and evidence-driven conclusions. Comfort reading open-source code and producing simplified alternatives to minimize code legacy and cognitive load. Effective use of developer-assist tools to amplify output while keeping quality high and code bloat at minimum. Produce services metrics that help us understand parallelism services can support in stable fashion, ensuring efficient hardware utilization. Propose scaling approaches based on application hardware utilization footprint & metrics. Familiarity with key Data Science, Machine Learning, or AI libraries is a bonus, but not mandatory, as long as the candidate can demonstrate the ability to quickly learn new concepts and paradigms. Product and Ownership perspective: Fast learning across new domains, with a knack for spotting and reducing unnecessary complexity. Team works on new products, understanding and implementing latest tech is paramount, learning fast. Product sensibility: start from a blank slate,