AI Engineer - Lead Software Engineer
Salary not listed • Jersey City, NJ, United States • Full-time
Posted 21d ago
No salary is listed. Many US states require employers to post a pay range, so ask about pay early.
Remote Work Policy
On-site
Employment Type
Full-time
Categories
AI Agent Engineer
About the job
As a Lead Software Engineer within Enterprise Technology, you will spearhead the architecture and hands-on implementation of scalable large language model (LLM) systems and agentic AI platforms tailored for enterprise use cases. You will design cloud-native solutions, establish robust evaluation and observability standards, and guide technical decisions across teams to enhance reliability, manage costs, and improve developer velocity. This role involves building and scaling production AI platforms that translate LLM capabilities into dependable, secure, and measurable business outcomes, partnering with product and engineering teams to design architectures, deliver reusable components, and elevate quality through strong engineering practices and technical leadership.
Responsibilities
- Lead the architecture and hands-on delivery of scalable, reliable agentic AI platforms for enterprise workflows.
- Design and build production-grade AI systems including agents, skills, memory patterns, guardrails, and tool-use orchestration.
- Architect retrieval and context-engineering approaches including embeddings, semantic search, grounding, summarization, and prompt/version management.
- Engineer cloud-native AI services on AWS using containers and serverless patterns, event-driven messaging, and distributed data stores.
- Optimize platform performance across latency, throughput, scalability, caching, context efficiency, and cost controls.
- Build well-governed APIs and integrations that connect AI capabilities to enterprise platforms, tools, and business processes.
- Establish evaluation, experimentation, regression testing, and observability frameworks to continuously improve quality and agent behavior.
- Define engineering standards for reliability, security, and safe AI operation across the platform lifecycle.
- Mentor senior engineers and influence engineering direction through code reviews, architecture forums, and cross-team technical leadership.
- Leverage enterprise-authorized AI coding assist tools to improve code quality, delivery speed, and productivity, validating outputs through peer review, automated testing, and secure coding standards.
Requirements
- Formal training or certification on software engineering concepts and 5+ years of applied experience.
- Experience architecting and shipping production large language model applications, including agentic workflows and tool integration patterns.
- Strong software engineering fundamentals with the ability to deliver cloud-native services using containers and serverless designs on AWS.
- Proficiency in designing distributed systems with asynchronous workflows, durable messaging, and scalable data access patterns.
- Experience building retrieval-augmented generation solutions (embeddings, semantic search, grounding) and managing prompt lifecycle/versioning.
- Demonstrated ability to implement evaluation and monitoring approaches for model quality, reliability, and safe behavior over time.
- Strong API design skills, including secure integration patterns and reusable platform capability development.
- Proven technical leadership skills, including mentoring, driving architecture decisions, and influencing cross-functional stakeholders.
- Hands-on experience using enterprise-authorized AI-assisted software development tools, critically evaluating, validating, and refining AI-generated outputs.
- Understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs/outputs, and adherence to resiliency and security expectations.