Job Summary

BMC is looking for a Senior Technology Solutions Specialist Agentic AI Solutions to help design, build, and scale Generative AI and Agentic AI capabilities that enable our Go-to-Market teams to work smarter, faster, and more effectively. In this role, you will build AI-powered applications, agents, copilots, automation workflows, and decision-support solutions that support areas such as sales productivity, account planning, deal coaching, competitive intelligence, pipeline inspection, forecasting, renewals, and executive decision-making. This is a hands-on engineering role focused on taking AI solutions beyond prototypes into secure, scalable, trusted, enterprise-grade production systems. You will partner closely with business stakeholders, data teams, IT, security, architecture, and product owners to deliver practical AI solutions that create measurable business impact.

Responsibilities

- Design, build, and deploy production-ready Generative AI and Agentic AI solutions for GTM business use cases.
- Build AI agents, copilots, and automation workflows to improve sales productivity, decision-making, and operational efficiency.
- Develop AI workflows that can retrieve trusted information, use tools, call APIs, reason over business context, and generate actionable recommendations.
- Build and maintain LLM-powered applications using Python and modern AI engineering practices.
- Implement Retrieval-Augmented Generation architectures using enterprise data, approved knowledge sources, vector search, and source-grounded responses.
- Develop prompts as managed, versioned, testable, and reusable engineering assets.
- Use agent and orchestration frameworks such as LangGraph, LangChain, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, or similar technologies.
- Work with vector databases and search platforms such as Pinecone, Weaviate, FAISS, Milvus, Azure AI Search, OpenSearch, or similar technologies.
- Integrate AI applications with enterprise systems such as CRM, data warehouses, APIs, knowledge bases, collaboration tools,



and GTM platforms.
- Build evaluation frameworks to test AI outputs for accuracy, groundedness, relevance, completeness, safety, and business usefulness.
- Implement monitoring and feedback loops to improve model performance, prompt quality, retrieval quality, cost, latency, and user experience.
- Design guardrails to reduce hallucinations, prevent unsafe outputs, protect sensitive data, and ensure responsible AI usage.
- Partner with IT, data engineering, architecture, security, and business teams to move AI solutions from prototype to production.
- Create reusable AI patterns, prompt libraries, evaluation templates, and implementation standards that can scale across multiple GTM AI use cases.
- Deliver trusted, secure, scalable, and helpful AI solutions that improve productivity, decision-making, and business outcomes across the GTM organization.

Requirements

- Bachelors degree in Computer Science, Engineering, Data Science, AI/ML, or a related technical field, or equivalent practical experience.
- 6+ years of experience in software engineering, data engineering, machine learning engineering, AI engineering, or related technical roles.
- 2+ years of hands-on experience building LLM, Generative AI, or Agentic AI applications.
- Strong programming experience in Python.
- Experience building production-grade applications, APIs, services, automation workflows, or data-driven solutions.
- Hands-on experience with LLM application development, prompt engineering, RAG architectures, vector search, tool use, and agent orchestration.
- Experience with AI frameworks such as LangGraph, LangChain, LlamaIndex, Semantic Kernel, AutoGen, CrewAI,



or similar tools.
- Experience with enterprise AI platforms such as Microsoft Copilot Studio, Azure AI Foundry, Azure OpenAI, AWS Bedrock, Google Vertex AI, or similar platforms.
- Experience with vector databases or retrieval platforms such as Pinecone, Weaviate, FAISS, Milvus, Azure AI Search, OpenSearch, or similar technologies.
- Strong understanding of hallucination mitigation, grounding techniques, prompt injection risks, AI safety, guardrails, evaluation, and monitoring.
- Experience integrating AI solutions with APIs, databases, data warehouses, enterprise systems, and business applications.
- Ability to translate business problems into practical AI solution designs.
- Strong communication skills and ability to work effectively with both technical and non-technical stakeholders.
- Hands-on builder mindset with the ability to move beyond demos and build enterprise-grade AI solutions that are grounded, tested, monitored, secure, and scalable.

Nice to have

- Experience building AI solutions for Sales, Revenue Operations, Customer Success, Marketing, Partner, or other GTM teams.
- Experience with CRM platforms such as Salesforce.
- Experience with cloud platforms such as Azure, AWS, or Google Cloud.
- Experience with data platforms such as Snowflake, Databricks, BigQuery, or similar technologies.
- Experience with AI observability, logging, tracing, model evaluation, feedback collection, and performance monitoring.
- Experience with prompt lifecycle management, including prompt versioning, testing, approval workflows, regression testing, and performance tracking.
- Experience with CI/CD, Git, DevOps, containers, secure software development, and production deployment practices.
- Familiarity with enterprise security, role-based access control, data privacy, governance, compliance, and responsible AI standards.
- Exposure to designing reusable AI engineering patterns that can scale across multiple enterprise use cases.

📌 Senior GenAI Engineer (Pune)
🏢 BMC Software
📍 Pune