Senior AI Engineer

About The Team / Organization Outscale Partners is a fully owned subsidiary of The Argenbright Group and was established in 2022. The group brings more than 45 years of experience in transforming labour-intensive, essential frontline services across industries. It has operations across the United States, the United Kingdom, Middle East and India, supporting clients through a strong combination of industry expertise, technology, and people-centric service models.

Outscale Partners focuses on delivering innovative workforce and service solutions that enhance operational efficiency and customer experience.

Work Mode: Hybrid

• Cab Facility: Company-provided cab for pick-up and drop within 50kms radius of the office ( As per company Policy)

Role Summary Reporting to the Senior AI Consultant , the AI Engineer will design, build, deploy, and operate AI systems across Unifi Service’s enterprise platforms.

The role spans the entire AI lifecycle — use-case identification, model and system design, production deployment, monitoring, optimization, and continuous improvement.

Core Responsibilities

• Build and integrate AI-driven capabilities into enterprise applications and workflows using leading LLM platforms.
• Design and implement Retrieval-Augmented Generation (RAG) architectures to enable AI systems to securely leverage internal knowledge and data sources.
• Develop and orchestrate AI agents capable of executing multi-step, decision-based business processes.
• Own production AI systems end-to-end, including deployment, versioning, monitoring, scaling, and cost optimization.
• Define, implement, and maintain evaluation metrics for AI quality, reliability, latency, and cost efficiency.
• Collaborate closely with Leadership, Product and Engineering teams to identify, prioritize, and deliver high-impact AI solutions.
• Ensure AI solutions follow enterprise standards for security, data privacy, reliability, and maintainability.

Must-Have (Non-Negotiable) Skills & Experience

• 7 to 8 years of overall software engineering experience, with 3 to 4 years of hands-on work on production AI / LLM systems.
• Strong proficiency in Python, with experience writing production-quality, testable, and maintainable code.
• Proven experience designing and implementing RAG pipelines, including document ingestion, embeddings, retrieval, and response generation.
• Hands-on experience with vector databases (e.g., Qdrant, FAISS, ChromaDb, or similar).
• Practical experience using LLM orchestration frameworks such as LangChain, LlamaIndex, Autogen, Haystack, or Semantic Kernel.
• Prior experience building AI solutions in SaaS or enterprise-scale software environments.
• Experience integrating with major LLM providers such as OpenAI, Anthropic Claude, or Google Gemini.
• Solid understanding of prompt engineering, context engineering (context window management), and output control techniques.
• Experience deploying AI systems to cloud environments (AWS, Azure, or GCP) using Docker and Kubernetes.
• Working knowledge of LLMOps & MLOps practices, including model versioning, CI/CD, monitoring, and rollback strategies.
• Experience in implementing guardrails in AI Solutions along with Observability.

Preferred / Nice-to-Have Qualifications

• Exposure to multimodal AI systems, model fine-tuning, or reinforcement learning from human feedback (RLHF).
• Familiarity with Model Context Protocol (MCP).
• Understanding of AI cost optimization, latency tuning, and performance benchmarking in production.
• Experience with domains such as eCommerce, Retail, HR, Finance, Legal, Compliance, etc

Language & Documentation Expectations

• All production AI code must be clearly documented, version-controlled, and supported by appropriate tests.
• AI pipelines, prompts, and agent workflows must include design documentation and usage guidelines.
• Each production AI system must have defined ownership, monitoring dashboards, and operational runbooks.
• Clear documentation of model limitations, assumptions, and fallback behaviours is mandatory.

What We Offer

• High-visibility role with direct access to senior leadership and decision-makers.
• Opportunity to design and own enterprise-scale AI systems with real business impact.
• Hybrid work arrangement, balancing flexibility with collaboration.

Must have skills

• RAG pipelines
• LLM orchestration frameworks
• vector databases
• Python
• prompt enginee…