Lead Software Engineer - AI Platforms
Role details
Job location
Tech stack
Job description
- Design and implement complex software components across backend services, APIs, and UI experiences using Java, Python, and React, applying sound engineering judgment and pragmatic architecture.
- Build and refine agentic capabilities using the Smart SDK, including tool integration, orchestration patterns, and safety/reliability guardrails suitable for production use.
- Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
- Develop and optimize RAG pipelines end-to-end (ingestion, chunking, embeddings, retrieval, reranking, prompt/response patterns), improving relevance, latency, and robustness with OpenSearch and continuous measurement.
- Write secure, high-quality production code and raise the bar through code reviews, debugging, and hands-on mentorship-improving maintainability, performance, and consistency across the codebase.
- Drive operational excellence by identifying recurring issues and implementing automation, preventative controls, and reliability improvements to reduce toil and improve system stability.
- Engineer data and search solutions using PostgreSQL (schema design, migrations, query tuning) and OpenSearch (indexing strategies, query relevance tuning) to support AI and analytics workflows
- Contribute to cloud-native engineering on AWS, partnering on infrastructure-as-code with Terraform and improving deployment safety, environment consistency, and observability.
- Participate in technical evaluation sessions with internal partners and external vendors-assessing architecture, technical depth, and fit within existing platforms and information architecture.
- Champion modern engineering practices and knowledge-sharing, contributing to communities of practice and accelerating adoption of leading-edge technologies.
Requirements
- Formal training or certification on software engineering concepts and 5+ years applied experience
- Strong hands-on expertise in Java/J2EE, Spring Boot, and microservices architecture, building secure, high-quality, production-grade systems.
- Proficiency with AWS, Terraform, GitHub, Jenkins, and modern developer tooling (e.g., GitHub Copilot).
- Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
- Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
- Databases: proficiency with relational databases (e.g., PostgreSQL, MySQL), NoSQL databases (e.g., DynamoDB, Redis, etc.), and GraphQL.
- Containerization: experience with Docker and container orchestration (ECS, EKS, or Kubernetes).
- Demonstrated experience developing, debugging, and maintaining software in a large corporate environment using one or more modern programming languages and database querying languages.
- Demonstrable ability to write high-quality code in one or more languages, with strong debugging and troubleshooting skills.
- Emerging knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.).
- Demonstrated expertise with monitoring/observability tools (e.g., Splunk, Datadog, Dynatrace, CloudWatch) and proven capability to lead high-performing teams by influence-driving innovation, maintaining strong team health, and owning the end-to-end performance cycle
Preferred qualifications, capabilities, and skills
- Experience across the full Software Development Life Cycle (SDLC), from design and implementation through testing, deployment, and production support.
- Exposure to agile engineering practices including CI/CD, application resiliency, and secure engineering.
Benefits & conditions
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.