Key Responsibilities

- Provide technical leadership for a team/workstream building multi-agent and multi-model AI systems

- Own architecture decisions and lead design reviews (Architecture Decision Records) for key AI initiatives

- Architect scalable, full-stack AI solutions spanning data engineering, model training/fine-tuning, and LLMOps

- Drive cost and performance optimization for AI systems running at enterprise scale

- Partner cross-functionally with Product, Data Science, Security, and Compliance to shape solution design

- Evaluate and select AI tools, frameworks, and vendors for the team

- Mentor and upskill engineers, fostering technical growth within the team

- Balance hands-on technical contribution with team-level planning and delivery accountability

Skills & Key Competencies

Must-Have Technical Skills

- Technical leadership of AI engineering workstreams or a small team

- Architecting complex multi-agent/multi-model AI systems at scale

- Full-stack AI expertise: data engineering, model training/fine-tuning, LLMOps, infrastructure

- Owns architecture decisions and design reviews (ADRs)

- Cross-functional partnership with Product, Data Science, Security, and Compliance

- Cost and performance optimization of AI systems in production

- Mentors and upskills engineers





Valuable-to-Have Technical Skills

- Experience building/owning internal AI platforms or agent frameworks

- Vendor and AI tool evaluation/selection

- Contribution to AI governance and compliance frameworks (GDPR, SOC 2, HIPAA-aware design)

- Experience in regulated or highly audited environments

Key Competencies

- Balances big-picture architectural thinking with a willingness to get into the weeds

- Decisive under ambiguity can make an 80%-confidence call and move the team forward

- Strong stakeholder management across technical and non-technical audiences

- Builds trust quickly with both engineers and cross-functional partners

- Invests genuinely in growing people, not just shipping features

- Holds a high technical bar without being a bottleneck

Required Experience & Qualifications

- 5+ years of experience, including demonstrated technical leadership of engineering initiatives

- Bachelor's degree in Computer Science, AI/ML, or a related field; Master's preferred

- Track record of owning architecture for at least one complex, multi-component AI system

- Experience partnering with security/compliance functions on production AI systems

📌 AI Software Engineer - Senior,Lead,Principal (Pune)
🏢 Fulcrum Worldwide Software
📍 Pune