Lead Software Engineer - AI / Full Stack

Role: Lead Software Engineer - AI / Full Stack
Location: Jersey City, NJ Duration: 6 Months Contract to Hire

• Expert in at least one technology and design technique as well as experience working across large environments with multiple operating systems/infrastructure for large-scale programs (e.g.,
  Expert Engineers) starting to be firm-wide resources working on clients projects across.
• Is multi-skilled with expertise across software development lifecycle and toolset.
• May be recognized as a leader in Agile and cultivating teams working in Agile frameworks.
• Sought out as coach for at least one technical skill.
• Strong understanding of techniques such as Continuous Integration, Continuous Delivery, Test Driven Development, Cloud Development, resiliency, security.
• Stays abreast of cutting edge technologies/trends and uses experience to influence application of those technologies/trends to support the business; may give speeches and outside the firm, writes articles.

Required Skills:

• 7+ years of end-to-end (full-stack) application development experience.
• Hands-on experience delivering system design, application development, testing, and operational stability.
• Proficiency orchestrating AI agentic workflows using frameworks such as Google ADK.
• Proficiency working with MCP, agent-to-agent (A2A) patterns, and sub-agents.
• Working knowledge of OpenID Connect (OIDC) and (OAuth) 2.0
• Experienced in REACT, RAG, REST and GraphQL APIs, databases, and real-time processing technologies.
• Advanced proficiency in React and at least one additional programming language.
• Strong command of all phases of the Software Development Life Cycle (SDLC).
• Advanced understanding of agile practices, including CI/CD, application resiliency, and security.
• Demonstrated expertise in software applications and technical processes within a core technical domain (e.g., cloud, AI/ML, mobile).
• Practical cloud-native experience (e.g., AWS, Cloud Foundry, Azure).
• Proven experience leading the effective use of approved AI-assisted software development tools (for coding, code review, test acceleration, and troubleshooting), including setting team standards for validating AI outputs for correctness, performance, and security.
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices.