AI Engineer
1 day ago
Wipro Romania, part of global IT and consulting leader Wipro Ltd., has grown significantly since 2007. With over 2000 employees from 21+ nationalities, it supports 50+ clients, offering a collaborative, inclusive work environment and professional growth opportunities.
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.
Required skills and experience
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.
Benefits:
- Attractive compensation package with a diverse set of social benefits (Private Pension Plan (Monthly Benefit budget, Medical insurance, Life insurance, Christmas bonus etc)
- Great career opportunity to work for one of the biggest brands in the world in a unique work environment
- Open-concept offices designed for both team work and relaxation with ping pong, billiards, foosball etc
- Child Birth Allowance
- Sport events sponsorship for employees
- Complex Record & recognition scheme ( both non-monetary and monetary options)
- Monthly subscription @ Bookster - the first modern library for companies in Romania
- Employee Referral Program with attractive incentive schemes
- Extra annual leave days depending on the total length of working experience at Wipro
- Growth opportunities through upskilling/ reskilling programs and a variety of learning and development platforms as well as through internal & external trainings and certifications
- Platform to actively participate and make an impact through Sustainability and Corporate Social Responsibility projects
This position offers a chance to be part of a forward-thinking company that values innovation and a progressive approach to technology. Interested candidates are encouraged to apply and join the team where they can make a significant impact.
Wipro is an advocate for positive change and conscious inclusion. As a global employer, we strive to create a diverse Wipro family by remaining committed to the development of our culture, diversity, equality, and inclusion in the workplace. All applicants welcome.
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