Junior Applied AI Engineer (LLM Systems)

Posted Yesterday
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11 Locations
Remote
Junior
Software • Consulting
The Role
Build and evaluate LLM-powered agents, including evaluation frameworks, guardrails, moderation, prompts, MCP servers, and tool integrations. Monitor quality, latency, performance, and costs with Langfuse; support fine-tuning and AI workflow prototyping. Develop FastAPI REST services in Python and collaborate with engineering, data science, and compliance teams to deliver secure, reliable, compliant AI solutions.
Summary Generated by Built In
Job Title

Junior Applied AI Engineer (LLM Systems)

Key Skills

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

Experience

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

Location

LATAM (Remote)

Mode

Remote

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

Key Responsibilities
  • 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.
Required Skills & Qualifications
  • 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).
Preferred Skills
  • 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.

Skills Required

  • 1-3+ years of experience in Machine Learning, Applied AI, Data Science, or Software Engineering
  • Experience working with Large Language Models and AI-powered applications
  • Knowledge of LLM evaluation techniques, 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, 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, unit testing, code reviews, and Git-based workflows
  • Advanced English communication skills, written and verbal
  • Experience developing MCP servers
  • Hands-on experience fine-tuning LLMs using LoRA or full fine-tuning
  • Familiarity with Small Language Models, 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

Encora Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Encora and has not been reviewed or approved by Encora.

  • Healthcare Strength — Health coverage is described as employer-provided in multiple locations, with private plans and family coverage highlighted in Spain and Mexico. Medical insurance quality is presented as a recurring bright spot alongside standard coverage.
  • Leave & Time Off Breadth — Time off includes paid holidays and PTO, with regional materials indicating additional leave provisions in certain countries. Leave is generally portrayed as conventional to generous depending on location.
  • Flexible Benefits — Work-from-home flexibility is frequently highlighted as a plus, though it varies by role and client needs. Remote and hybrid options are positioned as part of the overall package.

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The Company
Chennai
7,456 Employees
Year Founded: 1980

What We Do

Headquartered in Santa Clara, California, and backed by renowned private equity firms Advent International and Warburg Pincus, Encora is the preferred technology modernization and innovation partner to some of the world’s leading enterprise companies. It provides award-winning digital engineering services including Product Engineering & Development, Cloud Services, Quality Engineering, DevSecOps, Data & Analytics, Digital Experience, Cybersecurity, and AI & LLM Engineering. Encora's deep cluster vertical capabilities extend across diverse industries, including HiTech, Healthcare & Life Sciences, Retail & CPG, Energy & Utilities, Banking Financial Services & Insurance, Travel, Hospitality & Logistics, Telecom & Media, Automotive, and other specialized industries. With over 9,000 associates in 47+ offices and delivery centers across the U.S., Canada, Latin America, Europe, India, and Southeast Asia, Encora delivers nearshore agility to clients anywhere in the world, coupled with expertise at scale in India. Encora’s Cloud-first, Data-first, AI-first approach enables clients to create differentiated enterprise value through technology

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