Technical Delivery Lead

Endava

1d•Hybrid

About The Position

We are seeking a deeply technical, highly autonomous Technical Delivery Lead to drive the execution of strategic Artificial Intelligence, Agentic AI, AIOps, and Infrastructure Automation initiatives across a global enterprise environment. This role is ideal for a technical leader who can operate at the intersection of architecture, software engineering, AI engineering, SRE, cloud infrastructure, and technical delivery. The successful candidate will not simply coordinate projects—they will be hands-on with technology, code, architecture, technical decisions, and engineering execution.

Requirements

8+ years of experience leading complex technical projects, product delivery, software engineering initiatives, or cloud infrastructure programs within a global enterprise IT environment.
2+ years of experience leading AI, Agentic AI, AIOps, or AI-driven infrastructure platform deployments.
Strong hands-on knowledge of Python, including asynchronous programming and automation scripting.
Hands-on experience developing or integrating MCP (Model Context Protocol) servers and tool-calling architectures.
Strong understanding of LLMs, Agentic AI, multi-agent reasoning, tool calling, RAG, and AI orchestration frameworks such as LangChain or CrewAI.
Experience with Dynatrace/Davis AI, enterprise observability, AIOps, or self-healing infrastructure automation.
Hands-on experience with cloud platforms such as AWS and/or GCP.
Experience with CI/CD, Infrastructure as Code, automated testing, and SRE practices.
Experience working with enterprise monitoring and observability platforms such as Dynatrace, Splunk, or CloudWatch.
Strong understanding of infrastructure automation, SRE runbooks, incident management, and automated remediation.
Experience with data platforms and pipelines, including Snowflake, ETL, and data validation.
Ability to provide hands-on technical direction and code-review leadership while managing complex enterprise delivery.

Responsibilities

Lead end-to-end delivery of enterprise AI, Agentic AI, AIOps, observability, and infrastructure automation initiatives.
Drive development and deployment of Agentic AI platforms, multi-agent solutions, MCP-based architectures, and automated self-healing infrastructure.
Provide hands-on technical leadership, including Python development, asynchronous scripting, MCP server development, code reviews, and technical design.
Orchestrate cross-functional engineering teams across AI/ML, cloud, infrastructure, SRE, security, and application engineering.
Translate complex enterprise IT Infrastructure & Operations (I&O) environments into contextual schemas and tools that can be consumed effectively by AI agents.
Develop and implement automation for incident remediation, vulnerability management, observability, runbook execution, and infrastructure self-healing.
Work with enterprise observability platforms such as Dynatrace/Davis AI, Splunk, and CloudWatch.
Establish technical guardrails covering AI safety, data security, compliance, access controls, and responsible AI execution.
Drive CI/CD, Infrastructure as Code (IaC), automated testing, and cloud deployment practices.
Provide technical oversight of data pipelines, including ETL processes and Snowflake validation.
Conduct code reviews and establish engineering standards for AI agents, MCP servers, automation frameworks, and supporting services.
Track delivery milestones, technical risks, operational outcomes, and financial benefits while providing strategic visibility to executive leadership.