AI-augmented Software Developer

We are looking for a highly skilled AI-augmented Engineer with strong engineering experience and deep hands-on exposure to AI SDLC, autonomous agents, multi-agent systems, and AI orchestration frameworks. This role focuses on designing, building, and optimizing agentic AI systems — from autonomous agents and MCP integrations to complex orchestration layers for both new products and existing long-running platforms.

• 3–5+ years as a Software Engineer, including 1 year of extensive AI SDLC experience
• Strong practical development experience — JavaScript/TypeScript preferred, but Python, Java, Go are also acceptable
• Hands-on experience implementing AI orchestration frameworks, autonomous agents, multi-agent systems, and MCP integrations
• Solid understanding of the AI model lifecycle, prompting, evaluation loops, and continuous improvement
• Ability to work independently and own end-to-end technical delivery
• Consulting experience or strong client-facing communication skills
• Curiosity, experimentation mindset, and willingness to build greenfield AI solutions
• Experience running POCs, technical evaluations, or benchmarking approaches

Nice to have:

• Experience with vector databases, RAG, and embeddings
• Background in backend engineering, MLOps, or system design
• Understanding of LLM fine-tuning or model customization
• Experience integrating AI into production-grade applications

DESIGN & DEVELOPMENT:

• Design and implement Model Context Protocol (MCP) integrations and agent orchestration layers
• Build and maintain AI SDLC pipelines, tooling, and automation logic across the development lifecycle
• Implement agentic AI patterns, multi-agent workflows, and intelligent task automation
• Work with tools such as Claude Code, Cursor, Microsoft Copilot, and other AI engineering environments

RESEARCH & EXPERIMENTATION:

• Evaluate emerging agentic AI models, frameworks, and toolkits
• Build POCs and prototypes to benchmark scalability, reliability, and architecture fit
• Propose optimal designs based on hands-on research and clear analysis of trade-offs

CONSULTING & COLLABORATION:

• Work with product teams, architects, and clients to define requirements and shape AI SDLC solutions
• Communicate complex technical concepts clearly to non-technical stakeholders
• Guide clients on AI tool adoption (both greenfield and brownfield)