Senior Software Engineer

Quick Facts

• Role: Senior Software Engineer

• Focus: End-to-end AI-native product delivery in an engineering pod

Description

Senior Professional Software Engineer role designing, building, testing, deploying, and operating end-to-end product capabilities within an AI-native engineering pod. The position delivers AI, automation, and enterprise software solutions that modernize business operations, improve efficiency, and scale digital transformation. Work emphasizes systems thinking, specification-driven delivery, automated validation, and production engineering for secure, scalable, reliable outcomes.

Responsibilities

• Build full-stack capabilities across UI, APIs, services, workflows, data integrations, and cloud-native components
• Design and implement AI-enabled services including LLM integrations, retrieval pipelines, semantic search, embeddings, classification, ranking, workflow automation, and decision support
• Create prompt architectures and system instruction patterns, tool-use patterns, memory/context strategies, and agentic workflows with human-in-the-loop approvals
• Engineer context pipelines connecting enterprise knowledge, specifications, domain rules, data quality signals, and user intent
• Translate product intent, technical specifications, and acceptance criteria into validated, production-ready code
• Build evaluation harnesses, test datasets, quality thresholds, and feedback loops for accuracy and other quality dimensions (groundedness, consistency, latency, cost, reliability, safety, and risk)
• Own automated testing, CI/CD readiness, observability, auditability, traceability, incident response, rollback planning, and production validation
• Collaborate with engineering, product, TPM, architecture, data, security, operations, and domain teams to deliver solutions aligned to AI behavior, delivery, compliance, and business impact
• Use AI coding assistants, reusable context, specification-driven delivery, automated validation, and agentic workflows to generate, refactor, test, and document software responsibly
• Apply systems thinking to manage upstream/downstream impact, dependencies, security boundaries, failure modes, operational risk, compliance obligations, and long-term maintainability
• Identify and address responsible AI risks (hallucination, bias, privacy exposure, data leakage, insufficient explainability, unsafe automation, limited human validation)
• Maintain standards for security, privacy, accessibility, performance, resilience, and maintainability

Requirements

• Bachelor’s degree in computer science, software engineering, or related field; advanced degree preferred
• 3+ years of software development experience with ability to lead technical initiatives across teams
• Strong understanding of the full software development lifecycle
• Extensive experience with scalable systems (applications, platforms, internal tools, or developer infrastructure)
• Strong programming skills across multiple languages and stacks; able to work across frontend, backend, infrastructure, and DevOps as needed
• Required tech knowledge: Java and Angular (additional skills such as Python, JavaScript, TypeScript, PHP, Spring Boot, React, Spring Security, Hibernate, Node.js desirable)
• Experience driving adoption of new tools, practices, or platforms across engineering organizations
• Familiarity with AI-assisted development tools and workflows (e.g., GitHub Copilot, LLM APIs, agent frameworks)
• Ability to provide technical leadership through architectural guidance, code reviews, and hands-on pairing
• Strong fundamentals: programming, data structures, algorithms, APIs, distributed systems, cloud services, secure coding, testing, debugging, operational readiness
• Practical AI-native delivery experience: context engineering, prompt engineering, AI-assisted coding, agent orchestration, retrieval quality, model evaluation, output validation, responsible AI
• Exceptional communication skills for leadership and engineering collaboration
• Strong analytical thinking to evaluate trade-offs and make architecture decisions in ambiguous environments

Benefits

• Flexible working model
• Generous PTO and paid holidays; well-being and volunteer time off
• Up to 16 weeks paid parental leave and baby stipend
• Multiple medical plan options with mental health and wellness support
• 401(k) with company match and vesting after one year
• $400 annual well-being stipend and tuition assistance up to $5,250
• Recognition rewards, referral bonuses, exclusive discounts and more