Head of Engineering (AI Transformation & Core Systems)
- Source: Indeed
- ibroad solutions
- On-site
- State of Telangāna, India
- Full-Time
- C level
Job Description
Head of Engineering (AI Transformation & Core Systems)
Location: Hyderabad
The Mission:
Architect the Future of AI-Native Systems
We aren’t looking for a manager; we’re looking for a Transformer. This role is for a “Builder-First” leader who rose through the ranks of full-stack development by out-engineering the status quo. You are an expert at identifying the friction in traditional architectures and pivoting entire organizations toward AI-first engines where intelligence is the core driver of decision-making, not just a bolted-on feature.
Why This Role?
- Total Architectural Sovereignty: You have the mandate to dismantle legacy bottlenecks. If a process is slow, you have the authority to re-engineer it from the ground up using AI.
- AI Roadmap Ownership: You won’t just implement AI; you will define how it manages and scales our global business operations.
- Lead a “Special Forces” Team: Direct a high-density talent pool of world-class AI engineers where merit and innovation override hierarchy.
The Challenges Ahead:
- AI-Native Migration: Transition the org from static rule engines and manual CI/CD to self-healing systems and automated code generation.
- Non-Deterministic Real-Time Systems: Master the complexity of high-stakes, real-time trading environments using AI that performs under pressure.
- Solving the “Fast AI” Paradox: Integrate heavy LLMs and sophisticated tools without compromising on ultra-low latency.
- Full-Stack Precision: Maintain obsessive control over the entire lifecycle—from kernel-level memory management to high-performance frontend fluidity.
- Radical Optimization: Systematically replace human-led bottlenecks with AI-driven workflows.
Your Toolkit:
- Core Languages: Mastery of high-performance languages (C++, Rust, Go, or Python).
- AI/ML Depth: Proven expertise in LLM fine-tuning, RAG pipelines, Vector DBs (Milvus/Pinecone), and MLOps.
- Infrastructure: Deep knowledge of Kubernetes, distributed systems, and kernel-level optimizations for low-latency streaming.
Work Location: In person
Skills
- the-org
- toolkit
- cplusplus
- rust
- Golang
- Python
- Milvus
- Kubernetes
You missed this one - but you don't have to keep missing out. Try Club members get matched with open opportunities before they're gone, so you're always first in line, never last.
