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AI Engineer - Sr Lead Software Engineer
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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