Full Stack Engineer

Role Overview

We are seeking a Full Stack Lead Engineer who brings a strong foundation in software engineering combined with AI-enabled development practices. This role is ideal for a technology leader who has evolved across backend, frontend, cloud, and DevOps ecosystems, and is comfortable operating in complex, multi-technology environments involving both modern and legacy systems.

You will play a dual role — acting as a hands-on technical leader and a client-facing solution partner, driving end-to-end engineering excellence across product development initiatives.

Key Responsibilities

1. Technical Leadership & Delivery

• Lead end-to-end design and development of scalable, high-quality software solutions
• Work across full-stack layers: Backend, Frontend, APIs, integrations, and data systems
• Own and drive software release cycles including planning, development, testing, and deployment
• Ensure adherence to engineering best practices, coding standards, and quality benchmarks
• Conduct thorough code reviews (PR reviews) and enforce clean, maintainable architecture

2. AI-Augmented Engineering

• Leverage AI tools such as GitHub Copilot, Claude Code, Cursor, Codex, and similar platforms for:
• Code generation and acceleration
• Debugging and root cause analysis
• Automated code reviews and quality checks
• Drive adoption of AI-assisted development practices across teams
• Ensure responsible and efficient use of AI tools in engineering workflows

3. Solutioning & Architecture

• Collaborate with clients and internal stakeholders to understand business requirements
• Lead technical solutioning, system design, and architecture decisions
• Work across diverse technology stacks (e.g., .NET, Java, Node.js, Python, MERN)
• Design systems that integrate across cloud platforms, third-party services, and legacy systems

4. Team Leadership & Governance

• Lead and mentor a team of engineers across different technology stacks
• Provide technical guidance, resolve blockers, and ensure delivery excellence
• Establish and enforce development governance frameworks
• Drive continuous improvement in engineering practices, productivity, and quality

5. DevOps & Cloud Engineering

• Oversee CI/CD pipelines, release management, and deployment strategies
• Ensure system scalability, performance, and reliability on cloud platforms (AWS, Azure, or GCP)
• Work closely with DevOps teams to implement automation, monitoring, and observability

6. Client Engagement & Communication

• Act as a technical point of contact for clients
• Drive technical discussions, provide recommendations, and build client trust
• Communicate complex technical concepts clearly to both technical and non-technical stakeholders
• Contribute to pre-sales, estimations, and proposal solutioning

Required Skills & Experience

Core Engineering Expertise

• Strong experience in at least one primary stack: .NET / Java / Node.js / Python / MERN
• Proven experience across:
• Backend development (APIs, microservices)
• Frontend frameworks (React, Angular, Vue, Next.js, Typescript, Javascript etc.)
• Database systems (SQL/NoSQL)

Full Stack & Platform Exposure

• Hands-on experience with cloud platforms (AWS, Azure, or GCP)
• Exposure to DevOps practices (CI/CD, containerization, infrastructure as code)
• Experience working in multi-stack, distributed system environments

AI-Enabled Development

• Practical experience using AI tools like:
• GitHub Copilot, Claude Code, Cursor, Codex
• Strong understanding of AI-assisted coding, debugging, and review workflows
• Ability to integrate AI into engineering productivity and quality processes

Leadership & Client Skills

• Proven experience in leading engineering teams
• Strong communication and stakeholder management skills
• Experience in client-facing roles, including solutioning and technical discussions
• Ability to balance hands-on coding with leadership responsibilities

What We Are Looking For

• Engineers who have grown beyond a single technology stack
• Individuals who embrace continuous learning and cross-functional expertise
• Leaders who can drive engineering excellence while staying hands-on
• Professionals who are comfortable working in fast-paced, evolving technology landscapes

Success Metrics

• Delivery of high-quality, scalable solutions
• Effective adoption of AI-augmented engineering practices
• Strong client satisfaction and engagement outcomes
• Improved team productivity and engineering quality benchmarks