Jobs at TechTorch

Configure, implement, and optimize Salesforce CPQ solutions for clients. Gather business requirements, lead deployments, automate processes with Salesforce tools, ensure best practices, provide client support and training, maintain documentation, and manage multiple projects. The role also involves staying current with Salesforce CPQ features and related tools such as DocuSign and Conga.

Designs, develops, tests, integrates, and supports Salesforce solutions focused on Quote-to-Cash, CPQ, Revenue Cloud, contracting, billing handoffs, and service operations. Builds Apex, Lightning Web Components, Flows, integrations, automation, and scalable platform solutions. Troubleshoots production issues, manages deployments and releases, applies AI-assisted development practices, and collaborates with architects, consultants, business users, QA, and project managers.

Design, build, test, and deploy production-grade agentic AI systems using Python, LangGraph, LangChain, AWS Bedrock, and orchestration tools. Integrate AI agents with APIs and business systems, implement memory and retrieval, establish observability and safeguards, and develop reusable SDKs and templates. Collaborate directly with clients to define requirements, run experiments, and rapidly deliver reliable AI solutions using modern software engineering, cloud deployment, and CI/CD practices.

Supports Lead-to-Cash consulting engagements across CPQ, pricing, deal management, and revenue operations. Responsibilities include gathering requirements, defining future-state processes, creating functional specifications and user stories, facilitating client workshops, supporting AI-agent product ownership, and coordinating project delivery across onshore and offshore teams.

Designs and governs enterprise data architectures supporting analytics, reporting, operations, and AI initiatives. Responsibilities include data modeling, warehousing, integration pipelines, APIs, governance, quality, lineage, security, and architecture optimization. The role provides technical leadership and mentorship, guides cloud and big data technology decisions, develops proofs of concept and roadmaps, and supports client proposals and account growth. Collaboration with engineers, analysts, developers, and business stakeholders is central to delivering scalable, secure, high-performance data platforms.

The AI Developer will design, implement, and deploy AI agents and workflows, integrating advanced models and ensuring reliable performance in production environments.

Lead client-facing AI strategy and enterprise architecture engagements: run discovery workshops, design production-grade AI architectures (LLMs, RAG, agents, vector DBs), define governance and operating models, guide engineering teams, shape AI offerings, and mentor consultants to deliver measurable business outcomes.