Minimum Requirements :

- Strong understanding of LLMs, agent architectures, generative pipelines.

- Proven experience in delivering AI solutions in enterprise setting.

- Hands-on with backend engineering: Python/Node.js, &REST APIs.

- Familiar with prompt engineering, model fine-tuning, and retrieval-augmented generation (RAG).

- Excellent communication skills with business and technical stakeholders.

- Hands-on experience with LangGraph or similar AI agent frameworks.

- Proficiency with LlamaIndex, LangChain, or equivalent data processing libraries.

- Experience with vector databases (Pinecone, Weaviate, Chroma, etc.

- Working knowledge of multiple LLMs and their APIs (OpenAI GPT, Gemini, Claude).

- Experience with LLM observability tools (LangSmith, Weights & Biases, etc.

- Experience developing RAG (Retrieval-Augmented Generation) chatbots.

- Experience with coding agents and code generation systems.

Traditional AI/ML :

- Strong foundation in clustering, regression, classification, and forecasting.

- Proficiency with scikit-learn, PyTorch, TensorFlow.

- Experience with statistical analysis and experimental design.

- Knowledge of feature engineering and data preprocessing techniques.

- Understanding of multimodal AI.

Good To Have :

- Experience on AWS Bedrock/SageMaker.

- Fine-tuning experience with LLMs, rerankers, or embedding models.

- Self-hosting and deployment of open-source LLMs.

- Experience with BERT, transformer architectures, or computer vision models (YOLO).

- MLOps experience with MLflow, Weights & Biases, or TensorBoard.

- AWS Cloud platform certifications.

- Fine-tuning tools : LoRA, QLoRA, PEFT.

- Experience in building LLM BI solutions (natural language to SQL).

- Nice to have requirements to the candidate.

- Prior experience working on projects with a lot of PII data or working in Financial Services industry is a "Plus".

- Experience with multimodal AI systems combining text, image, and speech.

- Familiarity with AI Ethics, Safety, and Responsible AI Frameworks.

- Contributions to open-source AI projects or community involvement.

Perks :

- Opportunity to work on bleeding-edge projects.

- Work with a highly motivated and dedicated team.

- Competitive salary.

- Flexible schedule.

- Benefits package medical insurance, sports.

- Corporate social events.

- Professional development opportunities.

- Well-equipped office.

About :

- Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services.

- Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation.

- A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment in data, analytics, cloud & DevOps, application modernization and customer experience.

- Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.