What You'll Do:

- Design and develop agent orchestration frameworks and execution engines supporting complex AI-driven workflows.
- Design and optimize low-latency services supporting real-time conversational and voice interactions.
- Build reusable platform services, SDKs, APIs, and libraries that accelerate development of conversational AI applications.
- Design and implement Model Context Protocol (MCP) integrations and frameworks that enable secure, scalable access to enterprise tools, APIs, data sources, and agent capabilities.
- Develop reusable tool-calling, context-sharing, and interoperability services that support MCP-enabled agent ecosystems.
- Develop runtime services for text- and voice-based agent interactions, including context management, tool execution, memory, and state orchestration.
- Architect microservices and event-driven systems that integrate AI reasoning with enterprise systems such as customer, billing, network, and support platforms.
- Design mechanisms that safely translate model outputs into deterministic business actions and workflows.
- Collaborate with AI/ML engineers to integrate foundation models, retrieval systems, evaluation frameworks, and agent capabilities into production platforms.
- Drive platform reliability, scalability, observability, and performance across high-volume AI workloads.
- Establish software architecture standards, engineering best practices, and reusable design patterns for agentic systems.
- Contribute to technical strategy and platform evolution by evaluating emerging AI, orchestration, and distributed systems technologies.
- Mentor engineers and promote engineering excellence through design reviews, documentation, and knowledge sharing.

What You'll Bring:

- 7+ years of software engineering experience building distributed systems and cloud-native applications.
- Strong proficiency in Python or Java, with working knowledge of both preferred.
- Experience designing APIs, microservices, workflow engines,



or platform services.
- Experience building systems that integrate with LLMs, AI services, or conversational platforms.
- Experience designing highly available distributed systems and service-oriented architectures.
- Robust understanding of software architecture, system design, scalability, resiliency, and performance optimization.
- Demonstrated experience leading technical design discussions, driving architectural decisions, and influencing engineering direction across teams.
- Experience with cloud-native technologies, including containers, Kubernetes, and service-based architectures.
- Excellent problem-solving, debugging, and technical communication skills.
- Bachelors degree in Computer Science, Software Engineering, Information Systems, or a related field, or equivalent practical experience.
- Experience integrating AI systems with enterprise applications, APIs, tools, or data platforms through standardized integration patterns.

Must Have Skills:

- Python software engineering
- Distributed systems, APIs, and microservices
- LLM, AI service, and conversational platform integration
- Cloud-native architecture, containers, and Kubernetes
- Software architecture and technical leadership

Nice-to-Have:

- Experience building agent orchestration frameworks, workflow platforms, or AI execution systems.
- Experience with conversational AI, voice platforms, speech technologies, or real-time interaction systems.
- Familiarity with retrieval systems, vector databases, memory architectures, and evaluation frameworks.
- Experience designing internal developer platforms, SDKs, or reusable engineering frameworks.
- Knowledge of event-driven architectures, distributed workflows, and enterprise integration patterns.
- Experience with Model Context Protocol (MCP), agent tool-calling frameworks, or similar standards for connecting AI systems with external tools and services.
- Experience designing reusable tool integration frameworks, context management systems, or agent interoperability platforms.

📌 Engineer,AI (Hyderabad)
🏢 TMUS Global Solutions
📍 Hyderabad