Role : Senior Applied AI / LLM Engineer

Job Summary :

We are looking for a Senior Applied AI / LLM Engineer to develop and integrate Large Language Model (LLM) - powered capabilities into production applications and business workflows.

The role focuses on applying frontier AI models to real-world products, building agentic solutions, and ensuring the reliability, security, and performance of enterprise AI applications.

Key Responsibilities :

- Design and develop LLM - powered applications, AI agents, and services using models such as Claude, GPT, and Gemini.

- Integrate LLM capabilities into existing production applications, APIs, and business workflows using Python.

- Build agentic workflows, tool integrations, MCP - based solutions, and automation capabilities.

- Develop and maintain LLM evaluation frameworks to measure accuracy, reliability, latency, and cost.

- Assess existing machine learning and model - based solutions to identify opportunities for enhancement or migration to frontier models.

- Implement AI guardrails, personally identifiable information (PII) protection, audit trails, and security controls for enterprise and customer - facing applications.

- Monitor production AI behavior, identify failure patterns, and improve prompts, workflows, and model performance.

- Collaborate with Product, Engineering, Technology, and Operations teams to identify and deliver valuable AI use cases.

Required Skills and Experience :

- 6+ years of software engineering experience, including strong recent experience in Applied AI and LLM engineering.

- Strong proficiency in Python and backend/API development.

- Proven experience deploying LLM - powered features in production environments.

- Hands - on experience with OpenAI, Anthropic, Gemini, or similar frontier models.

- Strong understanding of prompt engineering, Retrieval - Augmented Generation (RAG), tool/function calling, AI agents, and LLM evaluation.

- Experience developing production - grade APIs, services, and integrations.

- Strong understanding of AI security, privacy, and enterprise guardrails.

- Ability to work with existing production codebases and develop new AI capabilities from the ground up.

Preferred Skills :

- Experience with Model Context Protocol (MCP) servers, integrations, and AI agents.

- Experience migrating traditional machine learning or model - based solutions to LLM - based approaches.

- Familiarity with LLM observability and evaluation frameworks.

- Experience working in regulated environments involving PCI, SOX, or similar requirements.

- Familiarity with AI development tools such as Claude Code, Kiro, Cursor, or similar platforms.

Ideal Candidate Profile :

The ideal candidate is a strong software engineer with hands - on experience delivering LLM - powered features in production.

They should understand how to integrate AI into real - world products, combine software engineering with AI evaluation, and prioritize reliability, security, privacy, and enterprise - grade controls.