Company Overview

Trianz is an applied AI solutions company that accelerates customer business transformation through AI-powered "Transformation Services as a Software Model." With 25+ years of transforming enterprises, we've evolved into a product-led, platform-driven organization serving global enterprises across Financial Services, Insurance, Healthcare, Hi-Tech, Manufacturing, and other industries.

With a global presence across 4 continents, our platform portfolio under the unified Concierto brand delivers end-to-end transformations including solutions for Migrate, Manage, Maximize, Modernize, Insights & Agentic AI, and SecOps, delivered through strategic partnerships with leading hyperscalers.

We're building the premier innovation-led organization in the digital transformation space through AI-first methodologies and data-driven excellence, RevolutionAIzing Transformations.

Role Overview

At Trianz, we are building sovereign, self-hostable AI products that enable enterprises to embrace AI while maintaining complete control over privacy, security, model access, and cost.

Our team is developing AI-native solutions for enterprise digital transformation, including a private conversational assistant for enterprise knowledge and productivity, as well as autonomous engineering agents capable of modernizing legacy enterprise applications.

We are looking for a Principal AI Engineer to define and drive the AI architecture powering these next-generation systems. This role spans AI research, evaluation frameworks, fine-tuning, inference optimization, enterprise-grade security, scalability, and production readiness.

This is a highly hands-on technical leadership role. You will be responsible for setting architectural direction, building production-grade AI systems, mentoring AI engineers, and staying at the forefront of emerging AI research and technologies.

Key Responsibilities

? AI Architecture & Technical Leadership

- Define and drive the overall AI architecture for enterprise conversational assistants and autonomous engineering agents.
- Establish technical direction for AI system design, scalability, security, evaluation, and deployment.
- Lead architectural reviews and guide engineering best practices across AI initiatives.
- Mentor and guide junior AI engineers while maintaining a strong hands-on engineering presence.
- Drive research adoption and translate emerging AI innovations into production systems.

? Advanced AI Systems & Agent Engineering
- Design and build sophisticated agentic AI systems capable of autonomous decision-making and workflow execution.




- Develop enterprise-scale conversational AI assistants with solid reasoning and task-execution capabilities.
- Build agent orchestration, planning, memory, tool usage, and complex multi-agent workflows.
- Architect and optimize agent evaluation frameworks for quality, reliability, and safety.
- Design AI solutions capable of handling complex, open-ended enterprise use cases.

? Fine-Tuning, Evals & AI Optimization
- Define and implement large-scale evaluation frameworks for enterprise AI systems.
- Lead model fine-tuning initiatives using techniques such as instruction tuning, LoRA, QLoRA, DPO, RLHF, and related methodologies.
- Build and optimize LLM-as-a-judge evaluation systems and benchmarking frameworks.
- Drive model performance improvements through experimentation, testing, and continuous refinement.
- Research and implement advanced approaches for improving reliability, reasoning, and accuracy.

? Self-Hosted Inference & Platform Engineering
- Design and optimize self-hosted inference architectures for enterprise deployment.
- Build scalable and cost-efficient AI infrastructure capable of supporting enterprise workloads.
- Optimize inference performance through quantization, caching strategies, model serving frameworks, and deployment enhancements.
- Work directly with inference stacks such as vLLM, Triton, and related technologies.
- Define deployment strategies supporting private, on-premises, and sovereign AI environments.

? Research & Innovation
- Stay current with cutting-edge AI research, open-source projects, engineering blogs, and industry advancements.
- Evaluate and implement emerging techniques across reasoning, fine-tuning, evaluation, retrieval, and agent systems.
- Prototype and validate innovative AI solutions to drive product differentiation.
- Contribute to long-term AI strategy and technical roadmap.

Ideal Candidate Profile

Experience

- Master's or PhD in AI, Machine Learning, Data Science, Computer Science, or related field.
- 5+ years of hands-on experience as an AI or Machine Learning Engineer.
- 2+ years of experience as a Principal Engineer, Architect, Technical Lead, or Technical Engineering Manager for enterprise AI products.




- Proven experience architecting and deploying production-grade AI systems.
- Experience leading technical direction across complex AI initiatives.

AI & ML Depth

- Strong understanding of AI and Machine Learning fundamentals.
- Production experience in multiple areas such as:
- Agent Systems
- Evaluation Frameworks
- Fine-Tuning
- Self-Hosted Inference
- Enterprise AI Security
- Deep knowledge of LLM architecture, optimization, and deployment.
- Experience building sophisticated AI evaluation and benchmarking systems.
- Strong understanding of reasoning frameworks, agent architectures, and autonomous systems.

Advanced AI Expertise

- Experience with instruction tuning, LoRA, QLoRA, RLHF, DPO, or related fine-tuning approaches.
- Experience designing and implementing LLM evaluation frameworks.
- Exposure to advanced AI architectures and optimization techniques.
- Understanding of inference optimization techniques such as quantization, speculative decoding, and caching strategies.
- Familiarity with pretraining, continued pretraining, reward modeling, or preference optimization is highly desirable.

Platform & Infrastructure

- Experience deploying and operating AI solutions beyond managed cloud AI services.
- Hands-on experience with inference frameworks, model serving, GPU infrastructure, and production AI platforms.
- Strong understanding of distributed systems and scalable AI infrastructure.

Enterprise & Product

- Experience developing enterprise software products requiring security, privacy, compliance, and customization.
- Ability to translate enterprise business requirements into scalable AI solutions.
- Experience building AI products intended for large-scale enterprise environments.

Mindset & Fit

- Passionate about solving complex and ambiguous technical challenges.
- Comfortable operating in fast-moving startup-style environments.
- Strong ownership mindset with the ability to balance research and execution.
- Continuous learner with a deep interest in cutting-edge AI innovation.
- Hands-on technical leader who enjoys coding, experimentation, and mentoring.

Nice to Have

- Experience in cloud migration, infrastructure modernization, IT operations, or enterprise transformation domains.
- Familiarity with conversational AI platforms and engineering agents.
- Experience with autonomous AI systems that perform enterprise workflows.
- Contributions to open-source AI projects, research, or technical publications.
- Experience leveraging AI coding agents and AI-assisted software development workflows.

📌 Principal AI Engineer (Bengaluru)
🏢 Trianz
📍 Bengaluru