AI Engineer

Volga Partners

. Design, build, and deploy production-ready Generative AI and LLM-powered applications .

Posted 10/6/2026full-timeRemote • IndiaMid-LevelSenior💰 ₹1,500,000 - ₹2,200,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and deploying Generative AI applications, with strong proficiency in Python and experience in building LLM-powered solutions. Capable of integrating various LLM platforms and optimizing AI systems for performance and reliability.

Highest-signal resume keywords

Python ProficiencyLLM Integration ExperienceRAG Pipeline DevelopmentAPI Development Using FastAPIAI Model Evaluation and Optimization

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Generative AI DevelopmentLLM Application DevelopmentRAG Pipeline OptimizationPrompt EngineeringBackend Service DevelopmentAPI DevelopmentModel Fine-TuningVector Database ExperienceSoftware Engineering FundamentalsTesting and Debugging

Soft Skills

Problem-Solving SkillsWritten/Verbal CommunicationCollaboration in Remote Teams

Tools & Technologies

FastAPIFlaskDockerAWSAzureGCPSQLKubernetesLangChainPinecone

Industry Keywords

Generative AILLMAI CopilotsChatbotsIntelligent AutomationSemantic SearchContext ManagementResponsible AI PracticesModel MonitoringAI Orchestration

Tech Stack

Tools & technologies

AWSAzureDockerFlaskGoogle Cloud PlatformKubernetesPythonSQL

About the role

Key responsibilities & impact

Design, build, and deploy production-ready Generative AI and LLM-powered applications
Develop chatbots, copilots, intelligent automation tools, and AI-assisted workflows
Build and optimize RAG pipelines using embeddings, vector search, and structured or unstructured data
Integrate LLM platforms such as OpenAI, Anthropic, Azure OpenAI, and similar providers
Develop backend services and APIs using Python, FastAPI, Flask, or similar frameworks
Design prompts, system instructions, and context-management strategies
Build scalable AI services from prototypes into production
Evaluate LLM outputs and improve quality, accuracy, latency, reliability, and cost
Monitor, troubleshoot, and optimize deployed AI systems
Implement evaluation, validation, guardrails, and error-handling strategies
Identify and resolve production issues and system regressions
Partner with engineering, product, operations, and business teams to translate requirements into practical AI solutions
Contribute to architecture decisions, technical discussions, and documentation
Stay current with Generative AI, LLMs, RAG, agentic AI, and emerging AI tooling
Evaluate and implement new AI models, frameworks, and techniques
Collaborate with engineering leadership, product teams, software engineers, backend developers, global AI research and development teams, and business stakeholders

Requirements

What you’ll need

3+ years of software engineering, AI/ML engineering, or related development experience
Strong proficiency in Python
Practical experience building applications using LLMs
Hands-on experience with RAG, embeddings, semantic search, and vector databases
Experience integrating LLM APIs such as OpenAI, Anthropic, Azure OpenAI, or similar platforms
Understanding of prompt engineering, model behavior, context management, and LLM evaluation
Experience developing APIs or backend services using FastAPI, Flask, or similar frameworks
Strong software engineering fundamentals, including Git, REST APIs, testing, debugging, and system design
Familiarity with Docker and modern development practices
Ability to take an AI use case from requirements through development, testing, and deployment
Strong problem-solving skills and written/verbal English communication
Ability to work effectively in a fully remote, globally distributed team
Experience building production AI copilots, chatbots, agents, or intelligent automation systems
Experience with LangChain, LlamaIndex, LangGraph, or similar AI orchestration frameworks
Experience with Pinecone, Weaviate, Qdrant, FAISS, Chroma, or similar vector databases
Familiarity with agentic workflows, tool/function calling, and multi-step AI systems
Experience with LLM fine-tuning, LoRA, or similar techniques
Experience deploying AI applications in AWS, Azure, or GCP
Familiarity with model monitoring, evaluation frameworks, guardrails, and responsible AI practices
Experience with SQL, CI/CD, Kubernetes, or model-serving infrastructure
Comfortable working Monday through Friday, 7:00 AM–4:00 PM Pacific Time, corresponding to overnight hours in India
Ability to work occasional weekends or schedule adjustments when business needs require

Benefits

Comp & perks

Contract and payment administration facilitated through Deel
90-day probationary period
Benefits eligibility upon successful completion of probation
Paid Time Off (PTO) in accordance with company policy
Holiday pay for company-observed holidays
Career growth and professional development opportunities