Sr Technical Analyst ( Go-To-Market and AI Technologies) (Salesforce/Azure)

Overview

Senior Technical Analyst (Go-To-Market and AI Technologies) (Salesforce/Azure) responsible for architecting and delivering technology that supports sales, marketing and deal-management processes, with a focus on enterprise CRM and AI solutions.

What you'll do

• Lead architecture, solution design, development, testing, deployment, integration and ongoing support across multiple products.
• Design and deliver technology supporting prospecting, account planning, opportunity management, pipeline and forecasting.
• Design and deliver technology supporting campaigns, account-based marketing, lead management, digital engagement and attribution.
• Design and deliver technology supporting proposals, RFPs, pricing, approvals, contracting and document generation.
• Design retrieval-augmented generation solutions using structured and unstructured enterprise data.
• Design AI evaluation frameworks covering accuracy, relevance, completeness, groundedness, hallucination, latency, cost and user acceptance.
• Implement human-in-the-loop controls, confidence thresholds, citations, approvals and exception-handling processes.
• Monitor production AI solutions for quality, drift, usage, performance, cost and unintended outcomes.
• Establish nonfunctional requirements for security, scalability, availability, maintainability, performance and disaster recovery.
• Diagnose complex production issues and establish monitoring, incident-management and support processes.
• Translate product roadmaps and business outcomes into technical strategies, architecture decisions, delivery plans and engineering backlogs.
• Lead design reviews, engineering standards, mentoring, quality oversight and resolution of cross-platform dependencies.
• Evaluate configuration, custom development, platform capabilities and third-party products and recommend the appropriate approach.
• Manage vendor and implementation-partner relationships.

What you'll need

• Minimum 4-year Bachelor's degree in computer science, information technology, engineering or related field.
• 5+ years of experience in enterprise application engineering, solution architecture, technical leadership or related technology roles.
• 2+ years designing and delivering AI, machine learning or generative AI solutions, including production implementations rather than prototypes alone.
• Experience leading architecture, solution design, development, testing, deployment, integration and ongoing support across multiple products.
• Experience delivering technology supporting sales, marketing and deal-management processes, including prospecting, account planning, opportunity management, pipeline and forecasting.
• Experience delivering technology supporting campaigns, account-based marketing, lead management, digital engagement and attribution.
• Experience delivering technology supporting proposals, RFPs, pricing, approvals, contracting and document generation.
• Strong experience with Salesforce or a comparable enterprise CRM, including platform architecture, security, automation, data models, APIs and integrations.
• Experience with enterprise AI platforms such as Salesforce Agentforce, Microsoft Copilot/Azure AI Foundry, Databricks or comparable technologies.
• Experience integrating CRM, customer-data platforms, data lakes, content repositories, marketing platforms, sales-enablement tools and deal-management systems.
• Experience leading internal engineers, external partners and multidisciplinary delivery teams.
• Demonstrated success modernizing platforms, reducing technical debt, improving reliability and transitioning solutions into sustainable operational support.
• Deep understanding of generative AI architecture, including large language models, agentic workflows, model orchestration, tool calling and multi-agent patterns.
• Experience designing retrieval-augmented generation solutions using structured and unstructured enterprise data.
• Knowledge of document ingestion, parsing, chunking, embeddings, vector search, semantic retrieval, metadata and enterprise knowledge management.
• Ability to determine when to use prompting, retrieval, deterministic automation, predictive models, shared agents or end-to-end AI solutions.
• Experience with prompt design, reusable prompt templates, grounding, context management and response-quality optimization.
• Ability to design AI evaluation frameworks covering accuracy, relevance, completeness, groundedness, hallucination, latency, cost and user acceptance.
• Experience implementing human-in-the-loop controls, confidence thresholds, citations, approvals and exception-handling processes.
• Strong knowledge of responsible AI, privacy, intellectual-property protection, model risk, data security and regulatory controls.
• Experience monitoring production AI solutions for quality, drift, usage, performance, cost and unintended outcomes.
• Understanding of model selection and the tradeoffs among commercial models, open models, platform-native AI and custom development.
• Ability to design reusable AI services and patterns that can support multiple GTM products.
• Strong solution- and integration-architecture skills, including APIs, event-driven patterns, middleware, authentication, authorization and identity management.
• Strong understanding of data architecture, master data, data quality, lineage, metadata and governance.
• Experience with cloud architecture, software engineering standards, source control, automated testing, CI/CD, DevSecOps and release management.
• Ability to establish nonfunctional requirements for security, scalability, availability, maintainability, performance and disaster recovery.
• Experience diagnosing complex production issues and establishing monitoring, incident-management and support processes.
• Ability to evaluate configuration, custom development, platform capabilities and third-party products and recommend the appropriate approach.
• Working knowledge of Agile delivery and product development lifecycle practices.
• Ability to translate product roadmaps and business outcomes into technical strategies, architecture decisions, delivery plans and engineering backlogs.
• Strong technical leadership, including design reviews, engineering standards, mentoring, quality oversight and resolution of cross-platform dependencies.
• Ability to collaborate effectively with product managers while maintaining clear accountability: product leaders define business outcomes and priorities; the technical lead owns how solutions are designed, built, operated and evolved.
• Strong communication skills and the ability to explain complex AI and architecture decisions to business and executive audiences.
• Ability to influence Sales, Marketing, Deal Management, Data, Security, Privacy, Legal and enterprise architecture stakeholders.
• Strong vendor and implementation-partner management skills.
• Ability to balance delivery speed with scalability, security, user experience, cost and long-term maintainability.

Nice to have

• Experience operating in a complex, global or regulated enterprise environment.

Details

• Location: Hyderabad, India.
• Work mode: Hybrid.
• Tasks, duties and responsibilities are not exhaustive and may be changed at the Company's discretion.