Senior Software Engineer Fullstack

Okta Okta · Enterprise · Bangalore, India · BT Go To Market Technology-173

Senior Software Engineer focused on building and evolving intelligent marketing technology solutions by integrating generative AI capabilities. The role involves architecting and developing AI-powered experiences using tools like Amazon Bedrock and LangChain, building robust backend services for LLM orchestration and RAG pipelines, and leading the design and delivery of complex marketing technology initiatives. Emphasis on prompt engineering, API design, CI/CD, and mentoring junior engineers.

What you'd actually do

  1. Design, build, and evolve intelligent marketing technology solutions that integrate Salesforce CRM with AWS services and modern generative AI capabilities.
  2. Architect and develop AI-powered experiences using Amazon Bedrock, LangChain, and modern LLM integration patterns to create context-aware, scalable, and mature solutions.
  3. Build robust backend services and integrations to support MarTech workflows, including LLM orchestration, prompt workflows, RAG pipelines, and other generative AI features.
  4. Lead the design and delivery of complex marketing technology initiatives from technical discovery through production deployment, ensuring scalability, reliability, and maintainability.
  5. Develop and refine prompt engineering strategies, grounding approaches, and AI interaction patterns that improve the quality, relevance, and safety of marketing technology AI experiences.

Skills

Required

  • 5+ years of professional software engineering experience
  • at least 3+ years in marketing technology platforms, enterprise integrations, or CRM-driven systems
  • Strong expertise in backend and application development using Python or Java, JavaScrip or TypeScript
  • Strong experience designing and building cloud-native solutions on AWS
  • Proven experience integrating LLMs and generative AI capabilities into production-ready applications
  • Experience building AI-powered backend services such as prompt orchestration layers, RAG workflows, retrieval pipelines, or other intelligent application patterns
  • Strong software engineering fundamentals, including distributed systems design, API development, testing strategies, code quality, and maintainable architecture
  • Experience building and supporting CI/CD pipelines, source control workflows, and automated deployments using tools such as GitHub and Gearset
  • Ability to lead architecture discussions, influence technical strategy, and make sound engineering decisions across multiple systems and stakeholders
  • Demonstrated experience mentoring engineers and helping teams improve engineering practices, technical quality, and delivery maturity
  • Strong working knowledge of Agile/Scrum delivery models
  • Excellent communication skills

Nice to have

  • Deep hands-on experience with Salesforce architecture and development
  • Experience with advanced prompt engineering, evaluation strategies, and optimization techniques for marketing technology AI applications
  • Familiarity with vector databases, embeddings, and Retrieval-Augmented Generation (RAG) architectures
  • Experience with LangGraph, LangSmith, agentic workflows, or related frameworks for orchestrating more advanced AI application behavior
  • Experience with containerization and orchestration technologies such as Docker and Kubernetes

What the JD emphasized

  • integrating LLMs and generative AI capabilities into production-ready applications
  • building AI-powered backend services such as prompt orchestration layers, RAG workflows
  • develop and refine prompt engineering strategies, grounding approaches, and AI interaction patterns

Other signals

  • integrating LLMs and generative AI capabilities into production-ready applications
  • building AI-powered backend services such as prompt orchestration layers, RAG workflows
  • develop and refine prompt engineering strategies, grounding approaches, and AI interaction patterns