Description
Role Overview :
We are looking for an Engineering Manager (AI) who combines strong people and delivery leadership with hands-on expertise in agentic AI and production-grade GenAI systems.
This role involves leading engineering teams, owning delivery for key client engagements, and shaping the architecture of intelligent AI solutions, including agentic workflows and voice-based AI systems.
This is a high-growth role with opportunities to lead marquee clients, brainstorm new-age AI solutions, and scale both teams and platforms.
Key Responsibilities
Engineering Leadership & Delivery :
- Lead, mentor, and grow a team of engineers, fostering a culture of ownership and technical excellence
- Own end-to-end delivery of AI-driven systems, from design through production
- Collaborate with product, data, and client stakeholders to define technical direction and execution plans
- Contribute to project planning, resourcing, timelines, and delivery commitments
AI & System Architecture
- Guide design and development of agentic AI systems, including single-agent and multi-agent workflows
- Oversee RAG pipeline implementation (document chunking, embeddings, retrieval strategies)
- Drive evaluation frameworks to measure agent accuracy, coherence, and task success
- Design scalable, reliable, and secure backend systems supporting AI applications
Advanced AI & Platform Practices
- Provide architectural guidance for voice AI systems (STT, TTS, real-time and multimodal agents)
- Ensure best practices across cloud deployment, containerization, CI/CD, security, and observability
- Stay current with emerging AI tools and trends and apply them meaningfully to client solutions
Required Qualifications
- 7+ years of experience in software engineering, with experience leading teams and delivering complex systems
- Proven people leadership and stakeholder management experience
- Strong proficiency in backend development (Python preferred; Java, Node.js, or Go acceptable)
- Solid understanding of LLMs, agent architectures, embeddings, and vector databases
- Experience designing RESTful APIs and scalable distributed systems
- Hands-on experience with cloud platforms (AWS/GCP/Azure), Docker, Kubernetes, and CI/CD
Preferred Qualifications
- Experience building production-grade agentic or multi-agent AI systems
- Exposure to voice AI or real-time AI systems
- Experience with AI evaluation, observability, and cost/performance optimisation
- Background in enterprise AI applications or AI-first startups
(ref:hirist.tech)
