Encora

SeniorAIBackendEngineer

₹25–45L ~AI est. Latin America Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Senior AI Backend Engineer at Encora. Skills: AI Backend Engineering, LLM Orchestration, Distributed Systems, AWS. Build production backend for Voice-to-Action AI pipeline. Operate production backend for Voice-to-Action AI pipeline”

Industry & Context.

Problems you'll solve

Analytical mindset; Problem-solving; Measurement focus; Reliability focus

What They're Looking For.

Must Have

7+ years of experience in backend engineering, Expertise in Python, Hands-on experience with FastAPI or similar backend frameworks, Understanding of REST API development, Understanding of service architecture, Understanding of distributed systems, Proven experience deploying and operating production systems on AWS, GCP, or Azure, Knowledge of Docker, Knowledge of CI/CD pipelines, Knowledge of cloud infrastructure, Knowledge of operational best practices, Experience building and maintaining production-grade AI/LLM systems, Proven track record of implementing instrumentation, evaluation, regression testing, and monitoring for non-deterministic AI components, Analytical and problem-solving mindset, Focus on measurement and reliability, Ability to quickly learn new domains, Ability to adapt to evolving technologies, Experience working in fast-paced engineering environments, Experience with changing requirements

Nice to Have

Deep experience with LLM orchestration frameworks, Deep experience with AI evaluation infrastructure, Experience with hosted LLM APIs, Experience with agentic coding workflows, Backend experience in TypeScript or Node.js environments, Experience with mobile voice pipelines, Experience with audio processing systems, Bilingual or multilingual NLP experience, Technical leadership capabilities, Mentorship capabilities

What You'll Do.

Build production backend for Voice-to-Action AI pipeline

Operate production backend for Voice-to-Action AI pipeline

Build STT and LLM orchestration services

Operate STT and LLM orchestration services

Design scalable backend systems

Design reliable backend systems

Develop instrumentation frameworks for AI workflows

Develop evaluation frameworks for AI workflows

Develop regression frameworks for AI workflows

Develop instrumentation frameworks for LLM-based systems

Develop evaluation frameworks for LLM-based systems

Develop regression frameworks for LLM-based systems

Define quality metrics

Monitor quality metrics

Establish feedback loops

Establish calibration practices

Optimize non-deterministic AI systems

Evaluate STT providers

Benchmark STT providers

Evaluate LLM providers

Benchmark LLM providers

Build scalable cloud-native services

Maintain scalable cloud-native services

Collaborate with backend engineering teams

Improve operational excellence

Improve platform scalability

Support adoption of AI-assisted engineering workflows

Support adoption of agentic engineering workflows

Contribute to backend platform initiatives

How You'll Work.

Team & Collaboration

Backend engineering teams; Cross-functional teams

Process & Methodology

Agile

Full Job Description

ob Title: Senior AI Backend Engineer Key Skills: Python, FastAPI, REST APIs, Distributed Systems, LLM Orchestration, AWS, Docker, CI/CD, AI Evaluation Frameworks, STT Pipelines Experience: +7 YOE Location: LATAM (Exclusive) Mode: Remote We at Coforge are hiring a Senior AI Backend Engineer (21736) with the following skill set. Key Responsibilities Build and operate the production backend for a Voice-to-Action AI pipeline, including Speech-to-Text (STT) and LLM orchestration services Design scalable and reliable backend systems within an existing distributed architecture Develop instrumentation, evaluation, and regression frameworks for AI workflows and LLM-based systems Define and monitor key quality metrics such as transcription accuracy, normalization drift, edit rate, and field-audio performance Establish feedback loops and calibration practices to optimize non-deterministic AI systems in production Evaluate and benchmark STT and LLM providers against internal performance metrics Build and maintain scalable cloud-native services using AWS, Docker, and CI/CD pipelines Collaborate with backend engineering teams to improve operational excellence and platform scalability Support the adoption of AI-assisted and agentic engineering workflows across the organization Contribute to broader backend platform initiatives after the Voice-to-Action pipeline reaches production readiness Required Skills & Qualifications 7+ years of experience in backend engineering with strong expertise in Python Hands-on experience with FastAPI or similar backend frameworks Strong understanding of REST API development, service architecture, and distributed systems Proven experience deploying and operating production systems on AWS, GCP, or Azure Strong knowledge of Docker, CI/CD pipelines, cloud infrastructure, and operational best practices Experience building and maintaining production-grade AI/LLM systems Proven track record of implementing instrumentation, evaluation, regression testing, an

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