Senior Applied AI / LLM Engineer

Role Overview

We are looking for a Senior Applied AI / LLM Engineer to build and integrate LLM-powered capabilities into production applications and business workflows. This role is focused on applying frontier models to real-world products, rather than model training or traditional data science.

Key Responsibilities

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

Integrate LLMs into existing production applications, APIs, and workflows using Python.

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

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

Analyze existing ML/model-based solutions and assess opportunities to replace or enhance them using frontier models.

Implement AI guardrails, PII protection, audit trails, and security controls for enterprise and customer-facing applications.

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

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

Required Skills & Experience

6+ years of software engineering experience,



with strong recent experience in Applied AI/LLM engineering.

Strong Python and backend/API development experience.

Proven experience shipping LLM-powered features to production.

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

Strong understanding of prompt engineering, RAG, tool/function calling, agents, and LLM evaluation.

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

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

Ability to work within existing production codebases and build new AI capabilities from the ground up.

Nice to Have

Experience with MCP servers/integrations and AI agents.

Experience migrating traditional ML/model-based solutions to LLM-based approaches.

Experience with LLM observability and evaluation frameworks.

Experience working with PCI, SOX, or other regulated environments.

Experience with AI development tools such as Claude Code, Kiro, Cursor, or similar.

Ideal Candidate A solid software engineer with hands-on production LLM experience who understands how to embed AI into products—not just use AI tools. The candidate should be comfortable with both engineering and AI evaluation, with a strong instinct for reliability, security, and enterprise guardrails.

📌 Senior Applied AI / LLM Engineer (India)
🏢 Codvo.ai
📍 India