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.