Tech Lead AI Engineer (IRC302738)

About the role

We are looking for a Lead AI Engineer to own the technical direction, design, and long-term health of the agentic AI solutions that accelerate our software development lifecycle. This is a hands-on leadership role: you will architect and build LLM-powered agents and internal AI tools, then scale them reliably and cost-effectively across an engineering organization of hundreds of people. Beyond delivery, you set the technical standard. You proactively identify gaps, challenge and improve existing solutions, guide other engineers and AI champions, and advise on build/reuse/buy and architecture decisions that keep our AI capability robust as it grows. You are the senior technical voice peers turn to - and someone who listens as carefully as they lead.

What you’ll bring

Bachelor's or Master's degree in Computer Science, Computer Engineering, Machine Learning, or a related field , or equivalent practical experience

6-8+ years of progressive software engineering experience, with a strong track record of designing, developing, and deploying scalable solutions in an enterprise environment

2+ years of hands-on experience building agentic AI and/or LLM-based applications in production with Python

Strong computer science fundamentals: data structures, algorithms, system design, major cloud platforms, and distributed systems - able to design and implement efficient solutions with ease

Proven experience with agent frameworks such as LangGraph / LangChain (or equivalents like LlamaIndex, AutoGen,n or the OpenAI Agents SDK)

Knowledge of enterprise SDLC tooling and ecosystems (e. g., GitHub Copilot, Claude Code)

Demonstrated success building and deploying agentic AI SDLC use cases for internal use: requirements engineering, development, testing, DevOps, and similar

The maturity and communication skills to lead technically, influence without authority, and align diverse stakeholders around the best solution

Nice to have

Experience standing up an internal AI platform, skill marketplace, or shared tooling used by many engineering teams

Cost-optimization experience: model routing, prompt caching, and token-usage management at scale

Experience defining security, permissions, and governance models (risk tiers) for AI agents

Familiarity with self-hosted / open-weight models and fine-tuning where appropriate. Experience mentoring or enabling a community of practice or champions network

Job Responsibilities

Technical leadership & strategy

Set the engineering standards, patterns, and guardrails for how agents are designed, built, evaluated, and operated.

Influence architectural discussions and make well-reasoned trade-off decisions across scalability, modularity, cost, and performance. nce

Design and build intelligent agents that plan, reason, and take action using LLMs

Implement RAG pipelines, long-term memory, action orchestration, and multi-agent collaboration.n

Deliver agentic use cases across the full SDLC: requirements engineering, development, testing, and DevOps.

Work on complex integrations that connect APIs, models, databases, and services for (near) real-time, agent-driven workflows

Scale, governance,e and collaboration

Optimize models and infrastructure for efficiency and cost-effectiveness (e. g., model routing, prompt caching, token budgets)

Maintain the internal AI tools - treat them as long-lived internal products

Establish observability, monitoring, and evaluation for agent operations and system interactions. ions

Define and enforce guardrails, permissions, and risk controls for what agents can and cannot ot do.

Troubleshoot and resolve complex technical issues affecting platform operations and performance

Work closely with engineers, domain experts, and AI champions across teams; listen to their needs and translate them into practical solutions.

Mentor and grow the technical capability of others so adoption becomes self-sustaining.

Department/Project Description

Broadband team works on 2nd generations of Harmonic (NASDAQ: HLIT) Cable Access products: actively developing the industry’s first software-based CCAP solution (“Cable OS”) and cloud native CMTS.

These solutions allow to cable operator companies to deliver the IP-based data, video, and voice services to millions of customers. Focus is given to CableOS, which will allow getting rid of the existing HW equipment and migrating to the cloud, saving customers the enormous expenses for the support of HW network equipment.

The system is based on microservice architecture and is running on general-purpose CPUs. It doesn’t require using ASICs and make possible to run the SW both on bare-metal servers as well as on the private cloud infrastructure. CableOS is a pioneer in DOCSIS software-defined networking (SDN) with all the benefits it gives to the service providers.

GlobalLogic team is involved in development, manual and automated testing, as well as in solution integration at customers’ headends and further technical support 24/7, providing professional services for Customers.

To learn more, please visit.

HTTPS://WWW.HARMONICINC.COM/BROADBAND/

HTTPS://WWW.GLOBALLOGIC.COM/UA/HARMONIC-AND-GLOBALLOGIC/