Sr AI Application Developer

Essential Duties And Responsibilities

• Design and build AI-powered applications using Large Language Models (LLMs) for enterprise use cases.
• Develop Retrieval-Augmented Generation (RAG) solutions using structured and unstructured enterprise data such as documents, manuals, tickets, ERP data, and knowledge bases.
• Build and orchestrate AI agents that can reason, plan, and interact with tools, APIs, and workflows.
• Implement guardrails for AI systems including prompt safety, data protection, hallucination mitigation, access control, and output validation.
• Integrate AI solutions with existing enterprise systems such as Salesforce, ERP platforms, data lakes, APIs, and internal applications.
• Partner with security and compliance teams to ensure responsible AI usage, data privacy, and governance.
• Prototype quickly, then harden solutions for production with monitoring, logging, evaluation, and performance optimization.
• Mentor and upskill existing developers on AI concepts, patterns, and best practices.

Required Skills & Experience

• 5+ years of full stack development experience.
• Strong software engineering background with experience building production-grade applications.
• Hands-on experience with modern LLM platforms such as OpenAI, Azure OpenAI, Anthropic, or similar.
• Practical experience building RAG pipelines using vector databases and embedding models.
• Experience with prompt engineering, prompt versioning, and evaluation techniques.
• Solid Python experience for AI development.
• Experience integrating AI services with REST APIs, microservices, and cloud-native architectures.
• Familiarity with cloud platforms such as AWS or Azure, including deployment, scaling, and security concepts.
• Understanding of data formats such as JSON, XML, and document-based data.
• Ability to translate business problems into AI-driven technical solutions.

Preferred Qualifications

• Experience with vector databases such as Pinecone, FAISS, Weaviate, or similar.
• Familiarity with frameworks such as LangChain, LlamaIndex, Semantic Kernel, or equivalent orchestration tools.
• Experience implementing AI safety controls, policy enforcement, and evaluation frameworks.
• Exposure to video or image models and multimodal AI use cases.
• Experience working in enterprise environments with security, compliance, and change management considerations.
• Prior experience mentoring or leading developers in new technical domains.