AI-First Software Development Lead (Business Analyst + Scrum Master + Hands-on Technical Lead)

About Us:

We are calling applicants on behalf of a software solutions company headquartered in East Brunswick, NJ. Incorporated in 2003, provides solutions across GRC, Technology, Procurement, Healthcare Provider and Oracle to customers globally. 

Position Summary

We are seeking a hands-on AI-First Software Development Lead who combines business analysis, Scrum Master / Agile delivery leadership and technical leadership in one role. The successful candidate will translate business problems into clear, testable requirements; guide a team through predictable delivery; and personally design, build, review, test and troubleshoot production-quality software using approved AI-assisted engineering tools.

This is not a purely coordination or architecture role. The lead remains technically hands-on and accountable for business value, delivery execution, engineering quality, team flow and production outcomes across the software development lifecycle.

Key Responsibilities

Business Analysis & Product Discovery

• Engage customers and users to understand business goals, pain points, workflows, constraints and measurable success criteria.
• Facilitate discovery and process mapping; document business rules, current/future-state workflows and functional / non-functional requirements.
• Convert needs into epics, user stories, acceptance criteria and process flows; prioritize the backlog and own UAT readiness.

Scrum Mastery & Agile Delivery

• Facilitate sprint planning, daily stand-ups, reviews, retrospectives, backlog refinement and release planning focused on outcomes.
• Maintain clear sprint goals, Definition of Ready / Done, manageable work in progress and transparent delivery forecasts.
• Remove blockers and manage dependencies, risks, decisions and escalations across business, engineering, QA, security and operations.
• Coach teams in Scrum / Kanban, estimation, collaboration and continuous improvement; communicate status and trade-offs clearly.

Hands-on Technical Leadership & Engineering

• Remain hands-on: write, debug and refactor production code, build APIs, integrations and UI components, and resolve critical technical issues.
• Translate requirements into pragmatic solution designs, modular architecture, interface contracts, data models and actionable technical tasks.
• Conduct code reviews and pair-programming; mentor developers and set standards for maintainability, testability and secure-by-design implementation.
• Promote automated testing, Git, code quality gates, CI/CD, deployment automation and production readiness.

AI-First Delivery, Quality & Responsible Use

• Embed approved AI tools into discovery, requirements, design, coding, testing, documentation, migration and support workflows.
• Use AI assistants for code, tests and documentation with human verification; check correctness, security, privacy, licensing and data exposure.
• Measure impact through cycle time, escaped defects, test effectiveness, rework and customer value—not AI usage volume alone.
• Maintain traceability from requirements to code, tests and release evidence, and follow Atlas / customer policies for data, access and intellectual property.

Stakeholder, Team & Production Ownership

• Act as an accountable point across business, delivery and engineering with clear decisions, ownership and escalation paths.
• Balance scope, quality, timeline, cost, technical debt and operational risk; support release notes, runbooks and post-release reviews.
• Build a culture of customer focus, flexibility, agility, precision, accountability and continuous learning.

Required Qualifications

• Bachelor’s degree in Computer Science, Engineering, Information Technology or a related discipline, or equivalent practical experience.
• Typically 8+ years of software application development and delivery experience, including hands-on coding and cross-functional team leadership.
• Experience in business analysis: stakeholder interviews, requirements elicitation, user stories, acceptance criteria, backlog management and UAT.
• Practical Scrum Master / Agile facilitation experience, including sprint ceremonies, impediment removal, team coaching and delivery improvement.
• Solid software engineering fundamentals in at least one modern programming language and application stack, with ability to review, debug and deliver production code.
• Experience delivering APIs, web applications, integrations, databases and automated tests; familiarity with Git, code reviews and CI/CD.
• Practical use of AI-assisted development tools in real engineering workflows, with disciplined verification and secure use.
• Strong communication, structured problem-solving and stakeholder-management skills; able to move effectively between business, delivery and technical detail.

Technical Skills

Business Analysis & Agile Delivery

• Requirements discovery, process mapping, user stories, acceptance criteria, backlog prioritization, UAT, Scrum, Kanban, sprint planning, flow metrics and retrospectives.

Programming & Application Engineering

• One or more of Java, C#, Python, JavaScript / TypeScript or equivalent; web frameworks, REST APIs, integrations, SQL / data modelling and debugging.

AI-First Development

• Approved coding copilots / LLM assistants, context and prompt design, AI-generated tests and documentation, evaluation and human-in-the-loop review.

Quality & DevOps

• Unit/integration/API testing, Git, CI/CD, code quality tools, observability, logging, deployment automation and root-cause analysis.

Security & Responsible AI

• Secure coding, least privilege, secrets handling, privacy, dependency scanning and responsible handling of customer data and intellectual property.

Preferred / Nice-to-Have Skills

• Experience with AI agents or Model Context Protocol (MCP), cloud-native platforms, containers, workflow automation, retrieval-augmented generation (RAG) or enterprise data platforms.
• Experience delivering software in regulated customer environments and using AI to improve engineering productivity while maintaining quality and security.

Core Competencies

• Business-first thinking and ability to connect requirements to measurable customer outcomes.
• Hands-on technical credibility and willingness to contribute production code—not just assign or review work.
• Facilitative leadership, collaboration, coaching, conflict resolution and decisive prioritization.
• Pragmatism, ownership, adaptability and comfort operating in a changing client environment.
• AI fluency balanced with critical thinking, confidentiality, quality discipline and human accountability.
• Agile execution, risk management, stakeholder communication and continuous improvement.
• Engineering quality, secure-by-design thinking and disciplined production ownership.
• Clear written and verbal communication with business and technical audiences.
• Problem solving, learning agility and effective cross-functional collaboration.
• Customer focus, precision, accountability and commitment to outcomes.

Success Measures

• Requirements are clear, prioritized, testable and traceable to business outcomes, reducing ambiguity and avoidable rework.
• Sprints and releases demonstrate improved predictability, healthy flow, timely risk escalation and stakeholder alignment.
• The lead contributes meaningful code and technical problem-solving while raising the quality and capability of the wider team.
• AI-assisted practices measurably improve cycle time, test effectiveness, documentation or rework without increasing security risk or escaped defects.
• Production releases meet agreed quality, security, performance and operational-readiness expectations; incidents result in durable corrective actions.
• Customers recognize responsive communication, ownership, precision and consistent delivery of business value.