SR Principal Software Engineer - Applied AI Engineering
On-siteJersey City, New Jersey, United States
Job Summary
Lead the execution of an AI-native SDLC and PDLC model across architecture, coding, security, testing, release, and observability phases. Operationalize agentic patterns and toolchains, including LLM orchestration, skills, context engineering, and MCP-based integrations, to materially reduce developer toil. Ensure responsible AI practices in production through guardrails, evaluation, monitoring, and auditable workflows. Partner with App Dev leaders and platform owners to identify high-impact use cases, validate value, and scale production adoption while driving alignment with GT/LOB stakeholders on control design and security approvals. Directly manage multiple technology areas and influence outcomes across a highly matrixed organization to achieve firmwide objectives in speed, scalability, and reliability. Establish portfolio-level standards for AI-orchestrated delivery workflows, release governance, and automated test modernization.
Required Qualifications
- Formal training or certification on software engineering concepts
- 10+ years applied experience
- Deep expertise in AI/LLMs and their application to software engineering workflows (coding, design, security, testing, release)
- Hands-on experience with agentic systems, tool/skill orchestration, and integration patterns (e.g., MCP, A2A, function/tool calling)
- Proven ability to lead cross-functional engineering delivery amid ambiguity, roadmap definition, backlog, dependency management, and stakeholder alignment
- Strong communicator with executive-level stakeholder management, able to translate between engineering depth and business outcomes
- Demonstrated prior experience influencing across highly matrixed, complex organizations and delivering value at scale
- Experience leading complex projects supporting system design, testing, and operational stability
- Experience with hiring, developing, and recognizing talent
- Deep understanding of responsible AI risk, controls, and resiliency/security expectations at scale, with demonstrated ability to advise senior leaders on safe adoption, portfolio governance, and reuse-first strategies
- Expertise in Computer Science, Computer Engineering, Mathematics, or a related technical field
Desired Qualifications
- Experience working at code level
- Experience with on-prem , cloud-native ecosystems and AWS services (e.g., EKS, Glue, S3, etc.,)
- Familiarity with modern data architectures and sharing patterns , data contracts/entitlements, and cost optimization
- Experience with secure SDLC practices and developer security tooling and vulnerability management metrics
- API-first production design and integration patterns; strong analytics and experimentation discipline
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