Manage, coach, and develop a team of AI/ML engineers, prompt engineers, and full‑stack developers delivering enterprise‑grade GenAI solutions.
Lead design and development of LLM‑based applications, RAG pipelines, intelligent agents, and AI‑driven workflow automation.
Ensure alignment with Enterprise Architecture, Responsible AI policies, LLM security controls, and all non‑functional requirements (latency, scalability, resiliency, monitoring).
Partner with architects to integrate cloud, data, and AI platform capabilities including model hosting, GPU compute, vector databases, and feature stores.
Identify and resolve AI‑specific technical barriers such as model performance bottlenecks, data quality problems, prompt degradation, and deployment issues.
Act as an escalation point for Agile teams, removing impediments and enabling innovation, experimentation, and continuous learning.
Conduct peer reviews and model reviews to ensure engineering quality and alignment with strategic AI technical direction.
Interpret, enforce, and optimize security, stability, and scalability guardrails; proactively identify and mitigate model, technology, and enterprise risks.
Collaborate with business leaders to validate AI/ML opportunities and translate them into actionable engineering roadmaps.
Provide L2 engineering support for production issues including model drift, integration failures, and data pipeline problems.

Requirements

4+ years of Specialty Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
2+ years of Leadership experience
4+ years of experience in AI/ML engineering management or related software engineering leadership role.
4+ years of programming experience (Python, Java, or similar).
4+ years of hands-on experience with AI/ML frameworks (TensorFlow, PyTorch, Scikit‑Learn, LangChain, LlamaIndex).
4+ years designing cloud‑native applications in GCP, AWS, or Azure.
4+ years of experience building LLM‑powered applications including embeddings, vector databases, model orchestration, and RAG pipelines.
4+years of experience with distributed and event‑driven systems (Kafka, Redis, MongoDB, Spark).
4+ years of Experience delivering APIs, microservices, and modern data solutions (Big Query, Snowflake, Dataproc).
4+years in test automation, performance evaluation, and enterprise‑grade AI validation.
4+years of Experience with UI/UX mockups (e.g., Figma) for AI workflow visualization.

Benefits

Health benefits
401(k) Plan
Paid time off
Disability benefits
Life insurance, critical illness insurance, and accident insurance
Parental leave
Critical caregiving leave
Discounts and savings
Commuter benefits
Tuition reimbursement
Scholarships for dependent children
Adoption reimbursement

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

AI/ML engineeringprogramming (Python, Java)AI/ML frameworks (TensorFlow, PyTorch, Scikit-Learn, LangChain, LlamaIndex)cloud-native application design (GCP, AWS, Azure)LLM-powered applicationsdistributed systems (Kafka, Redis, MongoDB, Spark)API developmentmicroservicestest automationperformance evaluation

Soft Skills

leadershipcoachingteam developmentcollaborationproblem-solvinginnovationcommunicationcontinuous learningpeer reviewescalation management