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 labor-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 : Permanent Remote

Shift Timings : 3.00 PM to 12.00 AM

Working Days : 5 days working (Mon to Fri)

Role & 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.

Preferred candidate profile :

- 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.