Senior AI Engineer

HCLTech is a global technology company, home to 220,000+ people across 60 countries, delivering industry-leading capabilities centered around digital, engineering, cloud and AI powered by a broad portfolio of technology services and products. We work with clients across all major verticals, providing industry solutions for Financial Services, Manufacturing, Life Sciences and Healthcare, Technology and Services, Telecom and Media, Retail and CPG, and Public Services.

Our purpose is to bring together the best of technology and our people to supercharge progress. We’re supercharging progress for everyone, everywhere – our clients, partners and their stakeholders, our people, communities, and the planet.

Role Summary

Work in a scaled Agile working environment

Be part of a global and diverse team;

Contribute to all stages of software development lifecycle;

Participate in peer-reviews of solution designs and related code;

Maintain high standards of software quality within the team by following good practices and habits

Use frameworks like Google Agent Development Kit (Google ADK) and LangGraph to build robust, controllable, and observable agentic architectures.

Assist in the design of LLM-powered agents and multi-agent workflows (planning, tool use, orchestration, memory, and human-in-the-loop)

Lead the implementation, deployment and test of multi-agent systems

Mentor junior engineers on best practices for LLM engineering and agentic system development.

Drive technical discussions and decisions related to AI architecture and framework adoption.

Proactively identify and address technical debt and areas for improvement in AI systems.

Represent the team in cross-functional technical discussions and stakeholder meetings.

Key Responsibilities

· Design and build complex agentic systems with multiple interacting agents.

· Implement robust orchestration logic (state machines / graphs, retries, fallbacks, escalation to humans).

· Implement RAG pipelines, tool calling, and sophisticated system prompts for optimal reliability, latency, and cost control.

· Apply core ML concepts to evaluate and improve agent performance, including dataset curation and bias/safety checks.

· Lead the development of agents using Google ADK and/or LangGraph, leveraging advanced features for orchestration, memory, evaluation, and observability.

· Integrate with supporting libraries and infrastructure (e.g., LangChain/LlamaIndex, vector databases, message queues, monitoring tools) with minimal supervision.

· Define success metrics, build evaluation suites for agents (automatic + human evaluation), and drive continuous improvement.

· Curate and maintain comprehensive prompt/test datasets; run regression tests for new model versions and prompt changes.

· Deploy and operate AI services in production, establishing CI/CD pipelines, observability, logging, and tracing.

· Debug complex failures end-to-end, identifying and document root causes across models, prompts, APIs, tools, and data.

· Work closely with product managers and stakeholders to shape requirements, translate them into agent capabilities, and manage expectations.

· Document comprehensive designs, decisions, and runbooks for complex systems.

Must-Have Qualifications

Core technical skills:

• Programming & software engineering:
• Strong proficiency in Python (core language features, packaging, testing, async, type hints).
• Very strong software engineering practices: version control (Git), unit/integration testing, code reviews, CI/CD.
• Experience building and consuming REST/gRPC APIs and integrating external tools/services.
• Machine Learning (good understanding):
• Understanding of core ML concepts: supervised/unsupervised learning, train/validation/test splits, overfitting, regularization, and common metrics (precision, recall, F1, ROC-AUC, etc.).
• Good undeerstanding of deep learning basics (neural networks, embeddings) and at least one ML/DL framework (e.g., PyTorch, TensorFlow, JAX, scikit-learn).
• LLMs & agentic AI (very strong understanding):
• Deep practical knowledge of large language models:
• Tokenization, context windows, temperature, top-p, system vs user prompts.
• Prompt engineering patterns (ReAct, chain-of-thought, tool-calling/tool-use).
• Fine-tuning / adapters / instruction-tuning, or experience with RAG as an alternative.
• Experience building LLM-powered applications end-to-end: from idea → prototype → production.
• Familiarity with safety and reliability considerations: hallucinations, guardrails, content filtering, privacy.
• Agentic frameworks (required understanding, experience preferred):
• Conceptual understanding of modern agentic frameworks and patterns (stateful graphs, multi-agent coordination, human-in-the-loop, memory, and evaluation).

Hands-on experience with at least one of:

o Google Agent Development Kit (ADK) – building multi-agent workflows, using its orchestration, tools, and evaluation features.

o LangGraph – designing graph-based, stateful agent workflows with cycles, branches, and durable execution.

· Candidates must be able to read, reason about, and extend ADK/LangGraph-based codebases.

· Direct production experience with both ADK and LangGraph is a strong plus.

Data & infra:

· Experience working with vector databases (e.g., Pinecone, Weaviate, pgvector, Chroma) for retrieval-augmented generation.

· Comfortable with SQL and basic data modeling.

· Experience deploying on at least one major cloud platform (GCP, AWS, Azure) and using managed services (e.g., serverless runtimes, container orchestration, secrets management).

Soft skills:

· Ability to translate ambiguous business requirements into concrete technical designs.

· Strong communication skills; able to explain trade-offs to both technical and non-technical stakeholders.

· Comfort working in an experimental environment with rapid iteration, but with a strong bias towards production quality and maintainability.

Nice-to-Have

Experience with:

· Vertex AI / Gemini or other hosted LLM ecosystems.

· Related frameworks and tools: LangChain, LlamaIndex, semantic search, evaluation frameworks (e.g., RAGAS, custom eval harnesses).

· Monitoring and observability stacks (OpenTelemetry, Prometheus/Grafana/NewRelic, Datadog, etc.).

Background in one or more of:

• Information retrieval / search.
• NLP (beyond LLMs): classic text processing, embeddings, semantic similarity.
• Security & compliance for AI systems (PII handling, access control, audit logging).
• Contributions to open-source AI projects, blog posts, or talks about LLMs/agentic systems.

Education & experience

3+ years of experience as Software Engineer / ML Engineer / AI Engineer, with at least 1-2 years working directly with LLMs in real applications (not just experiments or coursework).

Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field (or equivalent practical experience).

Why Us?

• We are investing in your growth, offering learning and career development opportunities at every level to help you find your spark;
• We offer a virtual-first work environment, promoting a good work-life balance and real flexibility;
• Our company is extremely diverse with representation of 165 nationalities;
• We offer the opportunity to work with colleagues across the globe;
• We offer comprehensive benefits for all employees;
• We are a certified great place to work and a top employer in 25 countries including Romania, offering a positive work environment that values employee recognition and respect;

What do we offer?

• 1066 RON monthly budget in Benefit Online Platform
• 25 vacation days/year.
• Life Insurance cover.
• The employees working on bank holidays will benefit either a paid day off in the next 30 days + 100% of the hourly base salary for that specific day OR 200% of the hourly base salary for that specific day.
• Childbirth allowance of 7000 RON after 1 year in HCLTech.
• In the first 8 weeks, the company will pay the difference of up to 100% for the parental leave granted to pregnant employees.
• Unfortunate events allowance of 7000 RON for first degree relative granted from day 1 in HCLTech.
• Internal trainings and certifications.

HCLTech is committed to protecting and securing the privacy and confidentiality of the Personal Data which it collects directly or indirectly from you when applying for a job at HCLTech either directly or through a third-party human resources agency. This notice (the “Notice”) outlines and explains how HCL Technologies Limited including its subsidiaries, local employing entities, associates, and affiliated companies [collectively referred to as “HCLTech”, “us,” “our”, or “we”] will process your Personal Data in accordance with applicable privacy legislation(s).

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