Junior Applied AI Engineer; LLM Systems

Junior Applied AI Engineer (LLM Systems)

• LLMs
• Generative AI
• AWS Bedrock
• Prompt Engineering
• AI Agent Evaluation
• Langfuse
• Python
• FastAPI
• MCP
• Guardrails & Moderation
• REST APIs
• Git

1-3+ years of experience in AI/ML Engineering, Applied AI, Data Science, or related fields.

LATAM (Remote)

Remote

We at Coforge are hiring Junior Applied AI Engineer (LLM Systems) (20848-10-1) with the following skill set.

• Design and execute evaluation frameworks for AI agents, including test datasets, LLM-as-a-Judge methodologies, human reviews, and regression testing.
• Build, configure, and optimize AI guardrails and moderation systems for regulated domains such as financial services and credit products.
• Develop, test, and continuously improve prompts based on evaluation results and production trace analysis.
• Create and maintain MCP (Model Context Protocol) servers and tool integrations that enable AI agents to interact with internal data and services.
• Support fine-tuning and evaluation of language models using domain-specific datasets.
• Prototype and validate AI workflows using System One models such as Jev and Laya for classification, routing, and verification tasks.
• Monitor AI system quality, latency, performance, and costs through Langfuse and implement improvement initiatives.
• Collaborate with Engineering, Data Science, and Compliance teams to ensure AI solutions are reliable, secure, and compliant.

• 1-3+ years of experience in Machine Learning, Applied AI, Data Science, or Software Engineering.
• Experience working with Large Language Models (LLMs) and AI-powered applications.
• Knowledge of LLM evaluation techniques, including benchmark datasets, scoring frameworks, and LLM-as-a-Judge approaches.
• Understanding of AI agent behavior across multi-turn conversations and tool-calling workflows.
• Experience with prompt engineering, structured outputs, and prompt optimization.
• Familiarity with AI safety concepts including moderation, prompt injection prevention, jailbreak mitigation, and guardrails.
• Hands‑on experience with AWS cloud services, preferably Amazon Bedrock.
• Experience with Langfuse or similar observability and evaluation platforms for LLM applications.
• Strong programming skills in Python.
• Experience developing REST APIs using FastAPI or similar frameworks.
• Knowledge of software engineering best practices including unit testing, code reviews, and Git‑based development workflows.
• Advanced English communication skills (written and verbal).

• Experience developing MCP (Model Context Protocol) servers.
• Hands‑on experience with fine‑tuning LLMs using techniques such as LoRA or full fine‑tuning.
• Familiarity with Small Language Models (SLMs), model distillation, and deployment strategies.
• Exposure to System One models such as Jev and Laya.
• Experience in financial services, fintech, banking, or other regulated industries.
• Knowledge of AI evaluation, observability, and production monitoring best practices.

Posted On 27-10-2026

At Coforge, we hire professionals based solely on their skills and qualifications and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality.