Director of Engineering (AI Solutions & Delivery)

techjays; Coimbatore District; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

techjays is seeking a Director of Engineering to own the engineering organization and drive the delivery of enterprise-grade AI solutions. This role bridges executive strategy with hands-on execution, managing Engineering Managers and Tech Leads to ensure AI systems ship on schedule, with reliability and quality.

You will lead high-throughput teams and shape operational discipline. You will foster an autonomous, high-performance culture, scale the department, and implement best-practice CI/CD,

Qualifications

• 14+ years in software engineering with a track record of multi-team delivery.
• 5+ years managing Engineering Managers or Tech Leads in high-growth or enterprise settings.
• Hands-on AI/ML experience delivering AI systems (LLMs, RAG, vector stores).
• Proven delivery track record from concept to launch on predictable schedules.
• Experience building distributed, cloud-native backends and scalable APIs.

Responsibilities

• Delivery Predictability & Execution: drive release schedules and hit 85%+ on-time delivery across teams.
• AI Quality & Governance: establish automated evals to test AI outputs before production; implement safety guardrails.
• Architecture & System Reliability: maintain high-availability SLAs and resilient infrastructure.
• Engineering Culture & Growth: manage and grow Engineering Managers/Tech Leads, scale the department.

Skills

Delivery leadership

AI/ML literacy

Software engineering

Cloud-native / distributed systems

Technical leadership

Tools

AWS

GCP

Azure

Job description

About the Job

We are looking for a Director of Engineering to own our engineering organization and drive the execution of our enterprise-grade AI solutions.

This is a pure execution and delivery role. You will bridge executive strategy with hands-on engineering execution, managing Engineering Managers and Tech Leads to ensure our AI systems ship on schedule, perform reliably, and adhere to quality benchmarks. If you thrive on building high-throughput teams, solving non-deterministic AI challenge pipelines, and creating operational discipline, this role is for you.

Key responsibilities

• Delivery Predictability & Execution
  • Own the Release Schedule: Turn long-term product roadmaps into predictable sprint cycles, hitting an 85%+ on-time delivery rate across all engineering teams.
  • Remove Roadblocks: Proactively detect and resolve cross-team dependencies, architectural bottlenecks, and resource constraints before they impact deadlines.
  • Process Discipline: Oversee modern CI/CD, automated testing, and agile workflows across all sub-teams to support continuous, low-risk deployments.
• AI Quality & Governance
  • Production Evaluation Suites: Establish automated evaluation pipelines (evals) to test AI outputs for hallucination rates, relevance, groundedness, and context accuracy before code hits production.
  • Safety & Guardrails: Implement circuit breakers, validation filters, and human-in-the-loop fallbacks to maintain system integrity when underlying LLMs produce unexpected responses.
  • Data & RAG Pipeline Excellence: Maintain vector stores, data ingestion feeds, and retrieval mechanisms to ensure the AI consumes clean, structured, and compliant context.
• Architecture & System Reliability
  • High Availability: Oversee application architecture to guarantee targeted Service Level Objectives (SLOs), including 99.9% uptime and low time-to-first-token (TTFT) latency.
  • Resilient Infrastructure: Partner with Staff and Principal Engineers to design resilient fallback logic when model APIs drop or experience rate limits.
  • Technical Standards: Maintain high standards across code review, observability, automated integration testing, and security compliance.
• Engineering Culture & Organizational Growth
  • Manager of Managers: Directly manage, mentor, and elevate Engineering Managers and Tech Leads, fostering autonomy and clear accountability.
  • Talent Acquisition: Attract, interview, and hire top-tier software and AI engineers to scale the department efficiently.
  • High-Performance Culture: Cultivate an engineering environment grounded in technical ownership, continuous improvement, and operational rigor.

Definitive Expectations (What Success Looks Like)

• First 30 Days Audit existing delivery pipelines, establish baseline AI evaluation criteria, and assume direct management of Engineering Managers/Leads
• First 60 Days Implement automated AI eval frameworks, streamline cross-team dependencies, and establish reliable release cadences.
• First 90 Days Achieve >85% sprint commitment completion, decrease production AI quality regressions, and stabilize system latency metrics.

Qualifications & Requirements

• Experience: 14+ years in software engineering with 5+ years managing Engineering Managers or Tech Leads in high-growth or enterprise settings.
• AI/ML Technical Literacy: Hands-on experience on delivering AI systems (LLMs, RAG architectures, vector databases, prompt engineering, or fine-tuning workflows).
• Delivery Track Record: Proven experience leading multi-team initiatives from technical concept through launch on predictable schedules.
• Systems Architecture Knowledge: Experience building distributed systems, cloud-native backend infrastructure (AWS/GCP/Azure), and scalable APIs.
• Leadership Focus: Strong ability to hold teams accountable to hard deadlines without sacrificing quality or developer morale.