Senior AI Engineer

About the role

You will architect and own the core orchestration layer that coordinates multiple AI agents in production environments at Turgon. You will design and implement the system responsible for routing, context management, and error handling across complex enterprise workflows. You will take direct ownership of transforming high-level business requirements into reliable agentic pipelines that meet strict operational standards. You will be responsible for building rigorous evaluation frameworks and monitoring systems to measure agent performance, accuracy, and cost in real-world scenarios. You will mentor junior engineers on prompt engineering patterns, agent communication protocols, and debugging methodologies. You will collaborate closely with product managers to translate abstract product visions into concrete agent architectures that are both powerful and maintainable. You will drive the lifecycle management of agents from initial design and prompt iteration through deployment, monitoring, and continuous optimization. You will ensure that our AI solutions scale reliably while maintaining low latency and controlled operational costs for enterprise customers.

Key facts

What you'll do

Design and implement the scalable orchestration layer that manages agent handoffs, context propagation, and state management across distributed workflows.

Build robust evaluation frameworks and automated testing suites to quantitatively assess agent outputs, hallucination rates, and task completion accuracy.

Optimize agent workflows for low latency and high throughput by analyzing execution traces and identifying computational or architectural bottlenecks.

Integrate enterprise-grade monitoring and logging solutions to provide full observability into agent behavior, decision paths, and resource utilization.

Implement cost management strategies by analyzing token usage, optimizing prompt templates, and designing efficient agent interaction patterns.

Develop and maintain comprehensive documentation for agent architectures, APIs, and operational playbooks to ensure long-term maintainability.

Lead debugging initiatives for complex agent failures by correlating logs, traces, and model outputs to identify root causes rapidly.

Establish best practices for prompt versioning, agent configuration, and environment management to standardize AI engineering processes.

Collaborate with data engineering teams to ensure agents have access to high-quality, well-documented data sources and integration points.

Partner with product teams to prototype new agent capabilities and validate technical feasibility before large-scale implementation.

Define and drive the adoption of architectural patterns that enable composable, reusable, and maintainable agentic systems.

Implement security and compliance controls specific to AI workflows, including data handling policies and access management for sensitive operations.

Conduct code reviews and technical design sessions to elevate the overall engineering standards across the AI platform team.

Explore and evaluate emerging large language models and agent frameworks to identify opportunities for technological advantage.

Requirements

You possess a Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a closely related technical field with a strong foundation in software engineering principles.

You have extensive hands-on experience with large language models and agent frameworks, demonstrating deep understanding of prompt engineering, tool use, and chain-of-thought reasoning patterns.

You are proficient in Python or other modern programming languages commonly used in AI engineering, with a proven track record of building and deploying scalable software systems.

You have implemented agentic systems or complex AI workflows that integrate multiple models, tools, and external APIs in production environments.

You demonstrate advanced problem-solving skills with the ability to dissect complex system behaviors, identify subtle bugs, and propose effective architectural solutions.

You have a strong grasp of software design patterns, data structures, and system architecture, enabling you to design robust and maintainable AI platforms.

You bring experience with cloud platforms and infrastructure tools, showing capability in deploying and managing distributed AI services at scale.

You exhibit a rigorous approach to testing, monitoring, and evaluating AI systems, with a clear commitment to reliability, performance, and cost efficiency in production.

Nice to have

Experience with reinforcement learning from human feedback (RLHF) or fine-tuning large language models for specialized agent behaviors.

Knowledge of containerization and orchestration technologies such as Docker and Kubernetes for deploying AI workloads.

Familiarity with vector databases and retrieval-augmented generation techniques for building context-aware agent systems.

Understanding of enterprise security standards and compliance requirements relevant to AI systems handling sensitive data.

Practical notes

This is a full-time position based in Delhi.

The role requires significant deep work focus and long-term commitment to building critical AI infrastructure.

Candidates must be available to work during standard business hours to support collaboration with international teams.