"Unlock your dream career with us. Connect with renowned employers, enjoy top-notch facilities, and thrive in a vibrant community.
Employer: McKinley Rice - Redrob
Position:
Work Days:
Years of Experience:
Community Location:
Employment Type:
CONNECT
Company Overview
McKinley Rice is not just a company; it's a dynamic community, the next evolutionary step in professional development. Spiritually, we're a hub where individuals and companies converge to unleash their full potential. Organizationally, we are a conglomerate composed of various entities, each contributing to the larger narrative of global excellence.
Redrob by McKinley Rice: Redefining Prospecting in the Modern Sales Era
anyone, not just enterprise giants, can access real-time, high-quality data on 700 M+ decision-makers, all in just a few clicks.
At Redrob, we believe the way businesses find and engage prospects is broken. Sales teams deserve better than recycled data, clunky workflows, and opaque credit-based systems. That’s why we’ve built a seamless engine for:
Precision prospecting
Intent-based targeting
Data enrichment from 16+ premium sources
AI-driven workflows to book more meetings, faster
Redrob is your growth copilot for unlocking warm conversations with the right people, globally.
How to become a part of our community:
Step 1:
30-Minute Recruiter Screen (Virtual)Step 2:
Technical Interview (Virtual)Step 3:
Be a part of the team at McKinley Rice!
EXPERIENCE
Duties you'll be entrusted with:
- Design, implement, and optimize LLM-powered AI solutions for domain-specific use cases.
- Develop and maintain MCP sidecar servers that integrate seamlessly with existing NestJS architectures.
- Expose internal business logic as MCP tools/resources for integration with AI-enabled clients.
- Build and manage MLOps pipelines for LLM lifecycle — training, deployment, monitoring, and retraining.
- Implement robust validation, observability, and security measures in both MCP tools and AI systems.
- Collaborate with cross-functional teams to integrate AI/LLM capabilities into production workflows.
- Maintain clear documentation, test suites, and deployment automation for AI and MCP components.
- Leverage third-party APIs and design scalable architectures to extend AI and MCP system capabilities.
Expectations from you:
Mandatory Requirements
Education:
- Bachelor’s degree or higher in Computer Science, AI, Data Science, or related fields.
AI/LLM Expertise:
- Development and deployment of Large Language Model (LLM)–based applications.
- Experience fine-tuning and integrating open-source and proprietary LLMs for domain-specific use cases.
- Proficient with LLM frameworks/libraries (e.g., Hugging Face Transformers, LangChain, LlamaIndex).
- Experience with prompt engineering, RAG (Retrieval-Augmented Generation), and agent-based AI systems.
MCP Server & Integration Skills:
- Strong understanding of the Model Context Protocol (MCP).
- Ability to expose NestJS services as MCP tools and resources with schema validation (e.g., zod).
- Knowledge of streamable HTTP transport for MCP where applicable.
- Proficiency in TypeScript/JavaScript and Python for MCP server development, LLM integration, and automation.
MLOps Expertise:
- Hands-on experience with MLflow, Kubeflow, or equivalent for model tracking, deployment, and monitoring.
- Implement CI/CD pipelines for LLM and AI application delivery.
- Experience in containerizing AI applications (Docker) and deploying on cloud platforms (AWS, GCP, Azure).
- Knowledge of scalable inference serving (e.g., FastAPI, BentoML, vLLM, Ray Serve).
Technical Skills
- LLM app development, LangChain, LlamaIndex, Transformers, spaCy, SmartDeviceBERT, Multimodal AI, Agentic AI, XAI.
Optional Skills
- Experience with causal inference models (SCM, counterfactual analysis).
- Projects involving Explainable AI (XAI).
Nice to Have
- Contributions to open-source MCP, NestJS, or AI/LLM projects.
- Familiarity with Claude Desktop/Code or other MCP host environments.
- Hands-on with multi-agent orchestration frameworks and multimodal AI integrations.
THRIVE
Some of the extensive benefits of being part of our team:
- We offer skill enhancement and educational reimbursement opportunities to help you further develop your expertise.
- The
Member Reward Program
provides an opportunity for you to earn up to INR 85,000 as an annual Performance Bonus. - The
McKinley Cares Program
has a wide range of benefits: - The wellness program covers sessions for mental wellness, and fitness and offers health insurance.
- In-house benefits have a referral bonus window and sponsored social functions.
- An Expanded Leave Basket including paid Maternity and Paternity Leaves and rejuvenation Leaves apart from the regular 20 leaves per annum.
- Our Family Support benefits not only include maternity and paternity leaves but also extend to provide childcare benefits.
- In addition to the retention bonus, our
McKinley Retention Benefits
program also includes a Leave Travel Allowance program. - We also offer an exclusive
McKinley Loan Program
designed to assist our employees during challenging times and alleviate financial burdens.
