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Job Description

Senior Lead Software Engineer role focused on building agentic AI platforms and LLM-enabled cloud services.

Responsibilities

  • Provide technical guidance to business and engineering teams by partnering with external teams to align on priorities, remove blockers, and drive delivery outcomes.
  • Develop secure, high-quality production code and lead code reviews; review, debug, and improve others’ code to raise engineering standards.
  • Own architecture and design decisions impacting product design, application functionality, and technical operations, including SDLC practices.
  • Act as a subject matter expert in one or more focus areas to support technical trade-offs and resolve complex problems.
  • Evaluate and introduce advanced technologies when appropriate, presenting clear rationale plus risk and benefit analysis.
  • Build and operate production-grade LLM applications, including agentic patterns and tool integrations for enterprise use cases.
  • Design and deliver cloud-native services on AWS using containers and serverless architectures with scalability and operational resilience in mind.
  • Implement retrieval-augmented generation (RAG) solutions using embeddings, semantic search, and context engineering to improve answer quality and control.
  • Build reliable service APIs and integrations with a focus on security, performance, and maintainability.
  • Drive adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (examples include AI-assisted code review/refactoring, test acceleration, release readiness, incident and root-cause analysis).
  • Establish measurable validation standards across the SDLC/TLM toolchain, including secure coding, peer review, and automated testing, while promoting reuse of proven patterns and automation.
  • Apply knowledge of Software Development Life Cycle toolchain capabilities, including approved AI-assisted development and automation, to scale automation value.

Requirements

  • Formal training or certification in software engineering concepts and 5+ years applied experience.
  • Strong Python engineering skills; experience with PyTorch or TensorFlow.
  • Expertise with vector storage systems and designing memory for agents.
  • Expertise developing long-running autonomous agents using tools, skills, and human-in-the-loop workflows.
  • Proven experience deploying LLM-backed services to production (APIs, microservices).
  • Deep MLOps experience, including CI/CD, monitoring, incident response, and model governance.
  • Cloud-native AI deployment experience on AWS or Azure, including cost and performance optimization.
  • Demonstrated commitment to responsible AI practices and operational excellence.
  • Strong communication and collaboration skills across product, risk, legal, and compliance teams.
  • Demonstrated experience designing and leading adoption of agentic AI-enabled development practices using enterprise-authorized tools, including human-in-the-loop validation, auditability/traceability of changes, and secure handling of sensitive data.
  • Strong understanding of responsible AI control expectations in engineering workflows, including security and resiliency implications, data sensitivity, and risk-based governance, with ability to influence senior technical leaders on safe scaling patterns and reuse.

Technologies

  • Python
  • PyTorch
  • TensorFlow
  • Vector storage systems
  • LLM-backed services
  • APIs
  • Microservices
  • CI/CD
  • AWS
  • Azure
  • Containers
  • Serverless architectures
  • Retrieval-augmented generation (RAG)
  • Embeddings
  • Semantic search
  • SDLC
  • TLM
  • Model governance

Preferred Qualifications, Capabilities, and Skills

  • Experience with fine-tuning, adapters, or custom evaluation frameworks.
  • Background operating AI systems in regulated environments (finance, healthcare, etc.).
  • Experience with prompt engineering and LLM orchestration.
  • Knowledge of safety filters, audit logging, and explainability in production systems.
  • Experience mentoring senior engineers and leading architecture discussions.
  • Demonstrated ability to influence technical roadmaps and priorities.
  • Location: Jersey City, NJ (onsite)
  • Salary: USD 175,750 - 260,000 per year
  • Experience: 5+ years

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