What are the responsibilities and job description for the AI Solution Development position at SWITS DIGITAL Private Limited?
Title AI Solution Development
Location Atlanta Syracuse Indianapolis Onsite
Job Description
Agentic AI is must to have
Agentic AI Multi Agents and MCP
Collaborate with engineering teams to design MCP based integrations and other integrations for internal tool development
Enable agent driven workflows that streamline engineering processes across software hardware and mechanical domains
AI Solution Development and Deployment
Design develop and deploy AI driven solutions for engineering applications
Design scalable production ready AI systems that integrate LLMs like GPT 4 Google Gemini Claude or Llama with internal data and APIs
Build complex workflows using frameworks like LangChain to manage prompt chaining memory and multi agent systems
Retrieval Augmented Generation RAG Implement vector databases such as Pinecone and FAISS to allow models to access and reason
Prompt Engineering Refine and optimize high quality prompts to ensure model outputs are accurate safe and aligned with business requirements
Model Fine Tuning Use techniques like LoRA Low Rank Adaptation to adapt foundational models for domain specific tasks
Evaluation and Monitoring Establish frameworks to test model performance for accuracy bias and reliability
Integrate AI capabilities into internal engineering tools to enhance productivity and automation
Take ownership design and lead projects for internal customer stakeholders
LLMOps and Testing
Apply LLMOps best practices for lifecycle management of large language models including CI CD pipelines monitoring and governance
Develop and execute testing strategies for AI applications to ensure reliability accuracy and compliance
Cloud AI Services Integration
Deploy and manage AI solutions on AWS ensuring scalability security and cost optimization
Implement containerization orchestration and serverless architectures for AI workloads
Collaboration and Documentation
Work closely with multidisciplinary teams in a global environment
Produce clear technical documentation and contribute to knowledge sharing initiatives
Location Atlanta Syracuse Indianapolis Onsite
Job Description
Agentic AI is must to have
Agentic AI Multi Agents and MCP
Collaborate with engineering teams to design MCP based integrations and other integrations for internal tool development
Enable agent driven workflows that streamline engineering processes across software hardware and mechanical domains
AI Solution Development and Deployment
Design develop and deploy AI driven solutions for engineering applications
Design scalable production ready AI systems that integrate LLMs like GPT 4 Google Gemini Claude or Llama with internal data and APIs
Build complex workflows using frameworks like LangChain to manage prompt chaining memory and multi agent systems
Retrieval Augmented Generation RAG Implement vector databases such as Pinecone and FAISS to allow models to access and reason
Prompt Engineering Refine and optimize high quality prompts to ensure model outputs are accurate safe and aligned with business requirements
Model Fine Tuning Use techniques like LoRA Low Rank Adaptation to adapt foundational models for domain specific tasks
Evaluation and Monitoring Establish frameworks to test model performance for accuracy bias and reliability
Integrate AI capabilities into internal engineering tools to enhance productivity and automation
Take ownership design and lead projects for internal customer stakeholders
LLMOps and Testing
Apply LLMOps best practices for lifecycle management of large language models including CI CD pipelines monitoring and governance
Develop and execute testing strategies for AI applications to ensure reliability accuracy and compliance
Cloud AI Services Integration
Deploy and manage AI solutions on AWS ensuring scalability security and cost optimization
Implement containerization orchestration and serverless architectures for AI workloads
Collaboration and Documentation
Work closely with multidisciplinary teams in a global environment
Produce clear technical documentation and contribute to knowledge sharing initiatives