Hire Top GenAI Engineers & RAG Specialists in India!
Years of experience
Customer satisfaction
What Makes Benchkart a Great Partner for Hiring GenAI Engineers / RAG Specialists?
Benchkart blends AI-driven talent intelligence, a deep vendor ecosystem, and Avance Group’s governance to deliver scalable, secure, and high-performing GenAI solutions.
Security-First Delivery
Private LLM deployments, governed retrieval workflows, data-compliance alignment, and enterprise-grade access controls.
Proven Talent Network
GenAI and RAG engineers sourced from our bench, passive AI-talent networks, and 2,000+ vetted partners.
Growth-Driven Engineering
Experts in LLM integration, knowledge automation, enterprise RAG architectures, AI agents, and safe model deployment.
Cutting-Edge Tech Stack
Developers bring hands-on expertise in:
Proficiency in OpenAI
Anthropic
Llama, Mistral
LangChain
LlamaIndex
vector DBs (Pinecone, Weaviate, FAISS)
embeddings
MLflow
Databricks, and cloud AI platforms
Services We Offer
Custom GenAI Application Development
RAG Architecture Design & Implementation
LLM Fine-Tuning & Domain Adaptation
Enterprise Knowledge Automation
Private & On-Prem LLM Deployment
AI Agents & Workflow Automation
Expertise of Our GenAI Engineers / RAG Specialists
A capability-first view of what you can expect from Benchkart’s Java engineering talent.
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Semantic search & embeddings
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Pinecone, Weaviate, FAISS, Milvus
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Document chunking, hybrid retrieval, ranking strategies
Roles & Responsibilities: RAG Specialists design end-to-end retrieval systems, optimize embeddings, configure vector databases, create custom retrievers, and ensure accurate, context-rich responses that eliminate hallucinations.
OpenAI GPT models
Llama, Mistral, Falcon
Prompt engineering & advanced prompting patterns
Roles & Responsibilities: GenAI Engineers build production-grade generative applications, design prompt frameworks, integrate tool-based function calls, manage context windows, and ensure reliable AI output aligned with business rules.
LoRA / QLoRA fine-tuning
Domain-specific tuning
Evaluation & benchmark testing
Roles & Responsibilities: They curate domain datasets, perform efficient fine-tuning, compare model variants, optimize for latency and quality, and deploy enterprise-ready tuned models for proprietary needs.
LangChain agents
Tool calling & planning
Multi-step workflow orchestration
Roles & Responsibilities: Engineers design LLM-driven agents capable of calling APIs/tools, performing reasoning chains, managing tasks, and automating complex business workflows in a safe and governed manner.
MLflow, Weights & Biases
Prompt/version governance
Latency, drift & hallucination monitoring
Roles & Responsibilities: They handle full lifecycle management deployment pipelines, evaluation suites, continuous monitoring, prompt testing, rollback strategies, and compliance-safe model governance.
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Azure OpenAI, AWS Bedrock, Vertex AI
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Serverless inference
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Enterprise security & cost governance
Roles & Responsibilities: Engineers architect cloud-native GenAI solutions, manage scalable inference endpoints, integrate identity/security layers, and ensure cost-optimized compute usage for production workloads.
How We Hire Developers
With a structured multi-stage hiring process, we onboard only high-calibre GenAI Engineers and RAG Specialists.
Skill Benchmarking
Thorough CV & background evaluation
Human Vetting
Interview with HR specialist
Experience Validation
Communication & soft-skills assessment
Cultural Fit
Technical interview with Senior GenAI Architect
Hire Developers from Benchkart
STEP 1 Inquiry
We understand your GenAI goals, RAG needs, domain requirements, cloud stack, and security constraints.
STEP 2 Developer Selection
AI-matched GenAI/RAG profiles curated from our bench, vendors, and passive expert networks.
STEP 3 Integration
Engineers integrate into your cloud platforms, vector stores, model endpoints, and sprint cycles seamlessly.
STEP 4 Scaling
Scale your AI program quickly with governed delivery, resource continuity, and flexibility.
Choose the Right Development Model for Your Business
Flexible models designed for GenAI, LLM, and RAG-enabled enterprise intelligence.
GenAI / RAG Team Augmentation
Add specialists instantly to accelerate development.
Dedicated GenAI & RAG Squad
A cross-functional team focused exclusively on enterprise AI, knowledge automation, and retrieval-powered solutions.
Full GenAI/RAG Development Outsourcing
We deliver discovery → RAG/LLM design → fine-tuning → deployment → monitoring end-to-end.
Top Reasons to Choose Benchkart for GenAI Engineer / RAG Specialist Hiring
Quality + speed + governance built for enterprise delivery.
Built on Avance Group’s Talent Engine
AI-driven matching with governance to ensure safe, compliant GenAI implementations.
Unmatched Speed 48-Hour Shortlists
Receive curated GenAI & RAG expert profiles within 48–72 hours.
Massive Vendor Ecosystem 2000+ Strong
Access India’s strongest network of generative AI, LLM, and knowledge automation engineers.
Wisestep ATS + CRM Skill-First Precision
AI ranks talent using embeddings depth, RAG experience, LLM orchestration skills, and cloud deployment expertise.
Bench-Ready GenAI Engineers
Experts in LLMs, embeddings, RAG workflows, LLMOps, vector search, and agent-based architectures.
Governed Delivery with Enterprise SLAs
Hallucination control, evaluation pipelines, performance benchmarks, and compliance frameworks.
Backed by Avance Group Global Trust
Operating across 14+ countries with proven excellence in AI and enterprise transformation.
Need a Dedicated GenAI & RAG Engineering Team?
Hire pre-vetted GenAI Engineers and RAG Specialists who build intelligent, retrieval-powered, and production-grade AI solutions from day one.
Shortlist in 48 hours. Onboarding in 5–10 days.
Operates across
Industries We Support for GenAI Engineer / RAG Specialist Hiring
Benchkart enables Generative AI transformation across major sectors.
BFSI & FinTech
Healthcare
E-commerce
Manufacturing
SaaS
Logistics
Telecom
Hospitality
FAQs
1. What does a GenAI Engineer / RAG Specialist do?
They design LLM-powered applications, build retrieval pipelines, implement embeddings, integrate vector databases, fine-tune models, and deploy safe, enterprise-ready AI systems.
2. What technologies do they use?
OpenAI, Llama, Mistral, LangChain, LlamaIndex, Pinecone, Weaviate, FAISS, MLflow, Databricks, Azure OpenAI, AWS Bedrock, and GCP Vertex AI.
3. Do they build RAG systems?
Yes, custom retrieval pipelines, document chunking strategies, embeddings, and hybrid search architectures are core skills.
4. Can they fine-tune LLMs?
Absolutely, including LoRA/QLoRA and domain-specific instruction tuning.
5. What does it cost to hire a GenAI Engineer in India?
Typically $45–$95 per hour, depending on LLM depth and enterprise-scale experience.
6. Do they support on-prem or private deployments?
Yes, open-source LLMs like Llama, Mistral, Falcon can be deployed privately.
7. Can I hire a full GenAI team?
Yes, including LLM Engineers, RAG Specialists, AI Agents Engineers, and LLMOps specialists.
8. How do they manage hallucinations?
Through retrieval-grounding, prompt constraints, model evaluation, and governance.
9. Can Benchkart deliver candidates in 48 hours?
Yes, shortlists typically arrive within 48–72 hours.
10. Why hire from Benchkart?
You gain vetted GenAI talent backed by AI-driven matching, vendor oversight, and enterprise-grade governance.
Get in Touch with Benchkart Reliable Tech Talent Delivery
We’re happy to answer any questions you may have and help you understand how Benchkart can support your technology hiring and delivery needs.
Your benefits:
- Vendor-verified
- Delivery-focused
- AI-driven
- Results-oriented
- Execution-ready
- Transparent
What happens next?
We schedule a quick call at your convenience
We understand your role, timeline, and delivery context
We activate the right talent path