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)
5. 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
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.
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.Apply to the position
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