Director of Engineering

About the Role

The Head of Delivery is a mission-critical leadership role with end-to-end ownership of

delivery across all ApexNeural client engagements. This is not a traditional PM or PMO role.

The position requires a hands-on technology leader who can drive complex AI and

enterprise engineering programs with accountability, speed, and execution rigor.

The ideal candidate brings a balanced blend of startup execution agility and enterprise-level

discipline, supported by strong AI and engineering fundamentals, a high-ownership mindset,

and long-term leadership maturity. This role plays a central part in ensuring predictable

delivery, high engineering quality, and strong client confidence across all programs.

Roles & Responsibilities

Own overall delivery outcomes across all client projects, including timelines, quality,

budgets, risks, and escalations

Own delivery financials including project margins, utilization, and cost efficiency

across engagements

Establish and enforce delivery governance, reporting structures, review mechanisms,

execution frameworks, KPIs, dashboards, quality gates, and compliance

mechanisms to improve predictability and delivery reliability

Plan, track, and manage project milestones, cross-team dependencies, and resource

allocation across multiple parallel initiatives

Drive continuous improvement in delivery velocity, execution consistency, and overall

process maturity

Act as the primary delivery owner in all client interactions and senior stakeholder

discussions

Build and maintain strong relationships with CXOs, product leaders, and program

stakeholders

Manage client escalations, scope alignment, expectation setting, and communication

clarity

Provide hands-on technical leadership across AI/ML, microservices, cloud platforms,

data engineering, and DevOps

Review and validate solution architecture, system design, sprint plans, and critical

technical decisions

Ensure engineering excellence through strong CI/CD practices, code quality, testing

discipline, observability, security, and performance standards

Proactively identify and mitigate technical and delivery risks, resolving critical

blockers on the ground

Lead and mentor engineering managers, solution architects, AI/ML engineers,

backend teams, QA, and DevOps teams

Build a performance-driven delivery culture with clear ownership, accountability, and

execution discipline

Enable efficient delivery across distributed teams while meeting aggressive timelines

and quality benchmarks

Balance startup agility and bias for action with enterprise-grade structure, scalability,

and governance

Requirements

15+ years of experience in software engineering, delivery management, and

leadership roles

Proven experience owning delivery for large, complex engineering or AI-driven

programs

Experience working in both startup environments (speed, ownership, ambiguity) and

MNCs (process, scale, structure)

Demonstrated job stability with at least one long-term role (45 years); ideally limited

to 34 organizations

Strong client-facing experience with senior stakeholder management and escalations

Bachelors degree in Computer Science (mandatory)

Strong hands-on technical understanding across:

AI/ML, LLMs, NLP, and MLOps

Microservices architecture and API platforms

Cloud platforms: AWS, GCP, or Azure

Data engineering, ETL/ELT pipelines

DevOps practices including CI/CD, Kubernetes, and Docker

System design, architecture reviews, and design patterns

Ability to review, challenge, and mentor engineering teams on technical and

architectural decisions

Excellent planning, execution, and problem-solving capabilities

Ability to manage multiple projects simultaneously under high pressure and tight

timelines

High ownership mindset with the ability to run delivery like a business

Strong communication, client-handling, and escalation management skills

Ability to act as a hands-on, workhorse execution leader for the organization

Preferred Qualifications

M.Tech / MS / PhD in Computer Science or a related field

Educational background from Tier-1 institutes (IIT / NIT / BITS) or reputed

international universities

Experience building or scaling delivery organizations in startups or mid-sized

technology companies

Prior experience in AI-first, enterprise product, or platform engineering environments