Gen AI ENGINEER

Generative AI (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 onAWS 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
  
  

Essential Functions

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.
  
  

Qualifications

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.
  
  

Would be a plus

Good To Have:

• Experience onAWS 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)
  
  

We offer

• 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 Us

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.

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