Senior Software Engineer II

This position performs complex research, design, and software development assignments in the design and delivery of production AI systems, including agentic workflows, LLM-powered pipelines, retrieval-augmented generation (RAG), and structured extraction services. The position provides direct input to project plans, schedules, and methodology for cross‑functional AI products; performs system design, typically across multiple systems and data sources; mentors more‑junior members of the team;

and works directly with business users and stakeholders to translate ambiguous, unstructured problems into measurable AI solutions.

Requirements: 5+ years of software engineering experience, including 2+ years building and shipping LLM-based or ML-based systems to production BS in Engineering/Computer Science or equivalent experience required Demonstrated track record of owning an AI feature or service end to end: design, evaluation, deployment, and monitoring Expert proficiency in Type Script/Node.js and/or Python; working knowledge of C#/.NET is a plus Hands‑on experience with LLM platforms and APIs (Azure OpenAI or equivalent), including prompt design, tool/function calling, structured outputs, and model selection tradeoffs Experience building RAG pipelines: chunking, embedding, hybrid retrieval, reranking, and grounding/citation Strong understanding of schema‑driven structured extraction from unstructured data (Zod, Pydantic, JSON Schema) and validation strategies Experience with evaluation frameworks for AI systems: golden datasets, LLM‑as‑judge, precision/recall on extraction tasks, regression testing of prompts and agents Strong SQL proficiency and understanding of relational and vector data storage (SQL Server, PostgreSQL, Elasticsearch/vector stores) Working experience with both AWS and Azure, including compute, storage, networking, IAM, and managed AI services;

containerized deployment (Docker, Kubernetes or equivalent), secrets management, and observability (token usage, latency, cost attribution) Strong knowledge of software development best practices, test‑driven development, and code review

• Design, build, and deploy production AI systems including agentic workflows, RAG services, and extraction pipelines across multiple business units
• Interface with business stakeholders and technical team members to scope AI use cases, define success metrics, and finalize requirements
• Write and review detailed technical specifications and architecture documents for complex AI system components
• Build and maintain evaluation harnesses; establish accuracy, latency, and cost baselines and monitor them in production
• Implement responsible AI practices: data handling, PII controls, hallucination mitigation, auditability, and human review where required
• Own cost and performance of LLM workloads, including model selection, caching, and usage attribution
• Build and maintain CI/CD pipelines and deployment automation for AI services across AWS and Azure environments
• Operate in Agile development environments while collaborating with key stakeholders across engineering, product, and business functions
• Mentor less‑senior engineers on AI system design, evaluation methodology, and production readiness

We know that your wellbeing and happiness are key to a long and successful career. These are some of the benefits we are delighted to offer:

• Health Benefits:
  
  Comprehensive, multi‑carrier program for medical, dental and vision benefits
• Retirement Benefits: 401(k) with match and an Employee Share Purchase Plan
• Wellbeing:
  Wellness platform with incentives, Headspace app subscription, Employee Assistance and Time‑off Programs
• Short‑and‑Long Term Disability, Life and Accidental…