Cognizant Romania is home to 2300+ creative technologists and is one of Eastern Europe's largest Software Product Engineering delivery networks. We serve global clients in several industries, including Banking & Financial Services, Insurance, Healthcare & Life Sciences, Communication Media & Technology, and Retail & MLEU (manufacturing, logistics, energy & utilities).

Cognizant Romania was established in 2018 when Cognizant acquired Softvision, a company founded in the late 1990s in Cluj-Napoca, Romania. We continue to build on our history as the preferred engineering partner for thriving Silicon Valley tech companies, now as a prominent Cognizant next generation studio.

We are seeking a talented and experienced AI/ML Engineer to join our team.

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

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).

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

Cognizant Romania Employee Benefits:

• Flexible Work Schedule - Outside of main work hours, you can create a schedule that suits your needs
• Hybrid workplace - Whether you like to work from home or go to the office, the choice is yours
• Annual Vacation Days - 26 days to relax, explore and spend time with loved ones
• Trainings, workshops, and certifications, unlimited Udemy subscription and more
• Private medical package
• Meal tickets
• Referral bonuses
• Life insurance
• Banking services
• Bookster

Please note that only suitable candidates will be contacted and that by applying to this role you are being informed about your personal data being processed by Cognizant.

You can find more details here: https://www.cognizant.com/us/en/privacy-notice