AI/ML Engineer

Job Description :Key Responsibilities :- Design and develop end-to-end AI/ML solutions with a strong focus on Generative AI, LLMs, and RAG architectures.- Build AI-powered solutions that improve employee productivity across People, Finance, and Legal functions.- Design, develop, and deploy autonomous and semi-autonomous AI Agents for complex business workflows.- Integrate AI Agents with enterprise platforms such as ServiceNow, Workday, and Salesforce.- Implement LLM integrations using models such as OpenAI, Anthropic, and Gemini.- Develop AI orchestration workflows using frameworks such as LangChain and LlamaIndex.- Integrate AI capabilities into existing enterprise applications through RESTful APIs and services.- Optimize AI/ML models for performance, scalability, reliability, and cost efficiency.- Design and implement data pipelines to support AI/ML applications.- Work with vector databases such as Pinecone, Milvus, and Weaviate.- Develop and maintain structured and unstructured datasets for AI applications.- Create and manage fine-tuning datasets to improve model accuracy and relevance.- Implement prompt engineering techniques and develop effective LLM prompts.- Establish model evaluation frameworks to measure accuracy, relevance, and performance.- Monitor AI systems for hallucinations, bias, security risks, and performance issues.- Ensure employee data privacy and security across AI solutions.- Follow best practices for AI development, deployment, monitoring, and versioning.- Collaborate with Product Managers, Business Systems Analysts, UX Designers, and data teams to identify high-impact AI use cases.- Convert business requirements into technical prototypes and production-ready AI solutions.- Research and evaluate emerging AI/ML technologies, frameworks, models, and industry practices.- Drive innovation in AI-powered Employee Experience solutions.Required Qualifications & Skills :- 5+ years of overall software engineering experience.- 2+ years of hands-on experience in AI/ML development.- Strong experience building applications powered by Large Language Models (LLMs).- Hands-on experience implementing RAG architectures and solutions.- Strong proficiency in Python.- Experience with AI/ML frameworks such as PyTorch, TensorFlow, or Scikit-learn.- Experience with LLM orchestration frameworks such as LangChain, LlamaIndex, or Haystack.- Hands-on experience with Vector Databases such as Pinecone, Milvus, or Weaviate.- Strong understanding of structured and unstructured data for AI applications.- Experience deploying AI/ML solutions on AWS, GCP, or Azure.- Familiarity with MLOps practices, including model monitoring, deployment, and versioning.- Strong understanding of RESTful APIs and API-based system integration.- Experience integrating AI solutions into complex, multi-system enterprise architectures.- Familiarity with enterprise platforms such as ServiceNow, Workday, or Salesforce is an added advantage.- Understanding of native AI/ML capabilities within enterprise platforms is a plus.- Strong knowledge of prompt engineering, model evaluation, and AI monitoring.- Understanding of AI security, data privacy, bias, and hallucination mitigation.- Strong problem-solving and analytical skills.- Ability to work effectively in ambiguous and rapidly evolving technology environments.- Excellent communication skills with the ability to explain complex AI concepts to technical and non-technical stakeholders. (ref:hirist.tech)