Coforge

AISoftwareEngineer

₹15–25L ~AI est. Latin America Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid+ candidates.

The Brief

“AI Software Engineer at Coforge. Skills: AI Software Engineering, Large Language Models, NLP, AWS. Design AI-driven applications. Develop AI-driven applications”

What They're Looking For.

Must Have

Bachelor’s degree in Computer Science, Engineering, Information Technology, Artificial Intelligence, Data Science, or equivalent practical experience, Software engineering experience, Hands-on experience building AI-enabled systems, Expertise with Large Language Models (LLMs), Expertise with Natural Language Processing (NLP), Expertise with AI application development, Hands-on experience using Claude (Anthropic) or similar AI models, Programming skills in Python or equivalent backend programming languages, Experience designing and deploying AI workloads in production environments, Hands-on experience with AWS cloud services, Experience working with Voice APIs, speech-based interfaces, or conversational AI systems, Understanding of REST APIs, Understanding of microservices architectures, Understanding of distributed systems

Nice to Have

Experience with AI model monitoring, Experience with AI observability, Experience with AI production optimization, Familiarity with scalable cloud-native AI architectures, Familiarity with orchestration patterns, Exposure to modern MLOps practices, Exposure to automation practices, Exposure to AI governance practices, Experience working in Agile product engineering environments

What You'll Do.

Design AI-driven applications

Develop AI-driven applications

Deploy AI-driven applications

Build AI workloads in production

Optimize AI workloads in production

Develop backend services

Develop distributed systems

Implement cloud-native AI solutions

Implement data pipelines

Implement best practices for performance

Implement best practices for reliability

Implement best practices for scalability

How You'll Work.

Team & Collaboration

Engineering teams; Product teams

Process & Methodology

Agile product engineering

Full Job Description

Job Title: AI Software Engineer Key Skills: Python, LLMs, NLP, Claude (Anthropic), AWS, Bedrock, SageMaker, Voice APIs, REST APIs, Microservices Location: Brazil Mode: Remote We at Coforge are hiring AI Software Engineer with the following skill set. Key Responsibilities Design, develop, and deploy AI-driven applications leveraging Large Language Models (LLMs), NLP techniques, and speech-based interfaces for scalable enterprise solutions. Build and optimize AI workloads in production using Claude (Anthropic), prompt engineering techniques, evaluation frameworks, and model optimization strategies. Develop scalable backend services, APIs, and distributed systems to support AI-enabled applications, voice interfaces, and intelligent automation workflows. Collaborate with engineering and product teams to implement cloud-native AI solutions, data pipelines, and best practices for performance, reliability, and scalability. Required Skills & Qualifications Bachelor’s degree in Computer Science, Engineering, Information Technology, Artificial Intelligence, Data Science, or equivalent practical experience. Software engineering experience, including hands-on experience building AI-enabled systems. Strong expertise with Large Language Models (LLMs), Natural Language Processing (NLP), and AI application development. Hands-on experience using Claude (Anthropic) or similar AI models for enterprise-grade AI solutions. Strong programming skills in Python (preferred) or equivalent backend programming languages. Experience designing and deploying AI workloads in production environments. Hands-on experience with AWS cloud services including Lambda, S3, API Gateway, Bedrock, SageMaker, or similar services. Experience working with Voice APIs, speech-based interfaces, or conversational AI systems. Strong understanding of REST APIs, microservices architectures, and distributed systems. Familiarity with structured/unstructured data pipelines, prompt engineering, model evaluation, and optimi

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