Job Title: Sr Applied AI Engineer Conversational & Agentic Systems
Location: Remote ( Dallas, TX )
Rate: $65/hr on C2C or 1099
Visa: H1B,L2EAD.EAD
Interview Mode: As per Client Process
Travel: Up to 50%
Position Overview
Tech Mahindra is seeking a Senior Applied AI Engineer to serve as the Agent Engineer and primary technical driver for critical Conversational AI and Agentic AI initiatives. The role focuses on transforming conversational AI prototypes into production-ready, scalable, secure solutions while owning the end-to-end engineering lifecycle.
The ideal candidate will have strong experience in software engineering, MLOps, cloud infrastructure, Generative AI, and Google Conversational AI, with hands-on expertise implementing and customizing the Google Conversational AI product suite.
Mandatory Requirement
- MUST HAVE: Hands-on experience implementing and customizing Google Conversational AI product suite
- Conversational Agents Gemini-powered CX
- Customer Engagement Suite (CES)
- Contact Center AI (CCAI)
- Candidates without hands-on Google CCAI / Conversational AI product experience should not be considered.
Key Responsibilities
- Serve as lead developer for complex Conversational AI and CX applications, transitioning prototypes into production-grade agentic workflows.
- Build and implement multi-agent systems and MCP-based solutions for enterprise use cases.
- Architect and code conversational flows integrating Gemini-powered Conversational Agents/CX, CES, and CCAI with customer infrastructure.
- Integrate AI solutions with APIs, legacy data sources, enterprise systems, and security environments.
- Build high-performance evaluation (Eval) pipelines and observability frameworks for agentic workloads.
- Optimize agent reasoning loops, tool selection, latency, accuracy, safety, and overall system performance.
- Ensure production-grade security, networking, scalability, and reliability.
- Identify technical challenges and recurring patterns and convert them into reusable modules or product feature requests.
- Work directly with customer engineering teams to establish strong development practices and ensure successful adoption.
- Lead technical discovery sessions and translate customer requirements into production-ready AI solutions.
Required Qualifications
- Bachelor's degree in Engineering, Computer Science, or related field, or equivalent practical experience.
- 5+ years of software development experience using Python or similar programming languages.
- Experience architecting AI systems on cloud platforms, preferably Google Cloud Platform.
- Experience deploying cloud resources using Terraform or similar Infrastructure-as-Code tools.
- Experience building structured and unstructured data pipelines using vector databases and RAG architectures.
- Experience developing full-stack applications integrated with enterprise IT infrastructure.
- Experience taking production-grade, customer-facing AI solutions from conception to launch.
- Experience leading technical discovery sessions with customers.
- Hands-on Google Conversational AI experience is mandatory.
Preferred Qualifications
- Master's or PhD in AI, Computer Science, or related technical field.
- Experience implementing multi-agent systems using LangGraph, CrewAI, ADK, or similar frameworks.
- Experience with agentic patterns such as ReAct, self-reflection, and hierarchical delegation.
- Experience debugging agent logic and optimizing tool selection.
- Experience tracing conversation IDs across microservices to troubleshoot production failures.
- Experience connecting AI agents to enterprise knowledge bases and optimizing RAG chunking.
- Knowledge of LLM-native metrics such as tokens/sec and cost-per-request.
- Experience optimizing state management and granular tracing.
- Experience troubleshooting live, high-traffic AI systems during critical production windows.
- Willingness to travel up to 50%.
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