About the Role

We are seeking a highly technical, strategic, and hands-on Head of Engineering to lead, scale, and drive engineering excellence across Ironbook's technology organization. The ideal candidate must possess deep architectural and engineering depth, with a proven track record of guiding complex technical transformations, rather than having a purely business-focused background.

In this role, you will be the ultimate engineering authority, overseeing our high-growth development teams and guiding the modernization of enterprise systems. A significant focus of this role will be directing complex, large-scale data migrations and platform modernizations, as well as integrating cutting-edge technologies like Generative AI, Large Language Models (LLMs), and cloud-native contact center platforms (e.g., Amazon Connect).

Key Responsibilities

1. Engineering Leadership & Governance (30%)

- Scale & Mentor Teams: Lead, recruit, and mentor a high-performing global engineering team across data engineering, cloud-native solutions, and AI practices.
- Technical Excellence: Instill a culture of architectural rigor, robust code quality, and engineering best practices.
- Strategic Vision: Align the technology roadmap with overall business objectives and delivery schedules, serving as a trusted technical advisor to internal leadership and enterprise clients.

2. Data Modernization & Migrations (30%)

- Data Platform Migration: Lead complex, enterprise-scale migrations from legacy environments (such as IBM DataStage or legacy SQL databases) to modern cloud data platforms (including Azure Databricks, ADF, and Snowflake), ensuring zero downtime and highly optimized pipeline structures.
- Lakehouse Architecture:



Architect and govern scalable enterprise data structures, leveraging Medallion architectures (Bronze, Silver, Gold), Delta Live Tables (DLT), and metadata-driven ETL pipelines.
- Engineering Depth: Troubleshoot and perform root cause analysis (RCA) on complex data pipelines, setting the standard for performance tuning (such as Spark tuning and SQL optimization).

3. AI, LLM, and Cloud Innovation (20%)

- Generative AI & RAG Solutions: Champion the integration of GenAI, LLMs, and Retrieval-Augmented Generation (RAG) frameworks to build automated, intelligent systems.
- AIOps & Automation: Integrate automated monitoring, incident detection, and remediation frameworks (AIOps/Agentic AI) to drive internal and external operational efficiency.
- Cloud-Native Architectures: Govern architectures across AWS and Azure environments, including specialized customer experience solutions (e.g., migrating legacy contact centers like Genesys, Avaya, or Cisco to Amazon Connect, as managed in our solutions practice).

4. Enterprise Delivery & Client Collaboration (20%)

- Client Front-Ending: Act as the primary technical authority during critical client discussions and high-stakes bids, translating complex business problems into elegant technical solutions.
- Cross-Functional Collaboration: Partner with Pre-Sales,



Recruiting (including talent acquisition pipelines), and Delivery teams to estimate project scope, evaluate resource capability, and ensure seamless delivery of client-facing projects.

Qualifications & Requirements

Experience & Education

- Degree: Bachelor’s or Master's degree in Computer Science, Information Technology, Engineering, or a related field.
- Leadership: 12+ years of overall software/data engineering experience, with 5+ years in strategic engineering leadership roles.
- Enterprise Portfolio: Proven history of leading large-scale technical projects, data migrations, or application modernization programs (ideally managing teams of 50+ engineers).
- Domain Expertise: Prior experience working within the Banking, Financial Services & Insurance (BFSI) domain—including hands-on knowledge of financial compliance, risk, policy/transactional systems, and data security—is highly preferred.

Technical Skills

- Data & Cloud Stack: Deep knowledge of Azure Data & AI services (Azure Data Factory, Azure Synapse, Databricks, PySpark, Snowflake, Microsoft Fabric) and AWS (S3, Redshift, QuickSight).
- AI & ML: Robust conceptual and practical understanding of GenAI, RAG, and AI-driven automation.
- Telephony & CX: Familiarity with modern cloud telephony migrations and architecture (SIP protocols, Amazon Connect) is a strong plus.

Soft Skills

- Elite communication skills, with the ability to explain complex technical and database architectures to non-technical business leaders and C-level stakeholders.
- A collaborative leader who thrives in rapid-paced, high-stakes environments.

📌 Head of Engineering (India)
🏢 Ironbook AI
📍 India