Salary
≈ $28k – $70k per year (Estimated)
Location
In office (Noida)
Seniority
Architect · 5+ years exp
Confirmed on the employer's own hiring board on Oct 14, 2026. First seen by Alion on Oct 13, 2026. EXL scores B on the Alion truth index.
Overview
Company
Impact
Profile match
EXL, legally ExlService Holdings, is a data analytics, AI and digital operations company headquartered in New York that runs outsourced business processes and builds data and AI solutions for insurers, healthcare organisations, banks, media and retail companies. Founded in 1999 and listed on Nasdaq, it has more than 60,000 employees across six continents, with large delivery centers in Noida, Gurgaon, Pune, Bengaluru and Chennai and a newer AI hub in Dublin. It hires data scientists and data engineers, GenAI and MLOps engineers, analytics managers, solution consultants and client partners, plus talent acquisition, finance and medical coding staff.
Required Skills
Technical Skills
- Strong knowledge of:
- Machine Learning & Deep Learning
- Large Language Models (LLMs)
- NLP (Natural Language Processing)
- Experience with:
- Python, APIs, microservices
- AI frameworks (TensorFlow, PyTorch, LangChain)
- Cloud platforms:
- Azure / AWS / GCP
GenAI-Specific Skills
- Prompt engineering
- RAG architectures
- Fine-tuning LLMs
- Vector databases (e.g., Pinecone, FAISS)
Soft Skills
- Problem-solving mindset
- Strong communication (explaining AI to non-technical teams)
- Strategic thinking
Key Responsibilities
1. Solution Architecture & Design
- Design end-to-end Generative AI solutions using LLMs (like GPT, Gemini, etc.)
- Define system architecture (APIs, pipelines, integrations)
- Choose appropriate models, frameworks, and cloud platforms
2. Model Selection & Optimization
- Evaluate and select foundation models / LLMs
- Fine-tune or customize models using:
- Prompt engineering
- Retrieval-Augmented Generation (RAG)
- Fine-tuning datasets
3. Integration & Deployment
- Integrate GenAI solutions into enterprise systems (CRM, ERP, apps)
- Deploy solutions using cloud platforms like:
- Azure AI / OpenAI
- AWS Bedrock
- Google Vertex AI
4. Data & AI Governance
- Ensure data privacy, security, and compliance
- Implement responsible AI practices (bias mitigation, explainability)
- Monitor model performance and accuracy
5. Collaboration & Leadership
- Work with business stakeholders to identify GenAI use cases
- Guide engineering teams on implementation
- Act as a technical thought leader in AI adoption
Qualifications
- Bachelor’s / Master’s in Computer Science, AI, Data Science, or related field
- 5-12+ years in software engineering, ML, or AI roles
Experience with enterprise-level systems
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