About the Company

AI Automation Squad – Technical Lead

About the Role

Role purpose Lead the technical delivery of high-value automation use cases that materially reduce operating cost and improve business efficiency within a product operating model environment. You will work as part of the Automation Squad, partnering closely with a progress-oriented Product Manager to deliver protected, measurable and supportable solutions. You will set the technical direction, standards and guardrails, while staying close to hands-on delivery where it adds value, ensuring that squad outcomes translate into real business savings and efficiency gains.

Responsibilities

- Location and remote working
- This role is available on a remote, hybrid or office-based basis in India working with team in UK
- Reporting line and key relationships

- Reports to
- Hiring manager (to be confirmed internally).
- Works closely with (day to day):

- Product Manager

- Developer Engineering

- Business outcome owners

- Architecture

- Data/Information Management

- Information Security

- Data Protection

- Legal/Compliance
- Subject-matter experts.

- Leadership
- Technical leadership and mentoring; may include line management depending on team structure.
- What success looks like (outcomes)
- A predictable delivery cadence from idea → discovery → prototype → production, with clear acceptance criteria and evidence of business value for each use case.
- Measurable reductions in operating cost and improvements in business efficiency (e.g. reduced handling time, error rate, or manual effort) for the processes supported by the squad’s AI capabilities.
- Reusable components and delivery patterns for generative and agentic AI (design, evaluation,



guardrails, deployment and monitoring) that accelerate future automation work.
- Solutions that are secure, compliant, cost-efficient, and operationally supportable.
- Transparent decisions: trade-offs (risk, cost, performance, maintainability) are explicit and backed by evidence.
- The squad delivers clear and measurable business outcomes, not just technical output.

- Key responsibilities
- 1. General responsibilities

- Advise the Product Manager on technical feasibility and cost implications during use case qualification, before any commitment is made.
- Partner with the Product Manager to shape, refine and deliver the prioritised backlog, translating needs into testable, outcome-focused acceptance criteria.
- Contribute to continuous discovery and innovation, ensuring technical realities and constraints are surfaced early.
- 1. Architecture & reusability strategy

- Own model, technical stack selection, orchestration patterns, data pipelines, integration architecture and security boundaries for squad use cases.
- Make explicit build vs buy vs reuse decisions for each use case, factoring in total cost of ownership and time-to-value.
- Define and maintain the reusable AI component library (prompt patterns, tools/agents, retrieval patterns, libraries, templates) that enables faster, cheaper delivery over time.




- Protect architectural integrity, with the authority to delay or reshape delivery where necessary to avoid unsustainable technical or cost debt.
- 1. Agentic system design & control

- Define how agents are scoped, constrained, monitored and governed within the organisation’s risk appetite.
- Enforce non-negotiable principles, including:
- Scope containment and least-privilege access.
- Human-in-the-loop checkpoints for material or irreversible decisions.
- Failure-mode mapping and safe-fallback behaviours.
- Audit trails and traceability.
- Reversibility of actions where possible.
- 1. Operational responsibilities

- Define technical evaluation frameworks – how output quality, safety and business impact (including cost and efficiency) are measured before and after deployment.
- Ensure monitoring, alerting and observability are in place before go-live, including quality, latency, usage, cost and incident signals.
- Own technical risk assessments for every use case, with special emphasis on regulatory, privacy and safety risk.
- Review and approve all technical designs produced by Developers, ensuring alignment with architecture, security, cost and quality standards.
- Manage technical dependencies with data, infrastructure and security teams, ensuring smooth integration and sustainable operations.
- Lead technical incident response where AI solutions are implicated, ensuring root causes are addressed and learnings are fed back into patterns and standards.
- Continuously optimise model, infrastructure and integration choices for cost-effectiveness without compromising safety or required performance.

📌 AI Lead (Gurugram)
🏢 Questhiring
📍 Gurugram