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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.
- Solid 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.

📌 AI/ML Engineer (India)
🏢 Glauben Technologies
📍 India