Principal Engineer

Exalans And Hunar Corporate Solutions; Thiruvananthapuram; On-site; INR 3,200,000 - 4,200,000; Full time

Job summary

Exalans And Hunar Corporate Solutions seeks a Principal Engineer to provide technical leadership across AI-powered cloud-native solutions. You will shape architecture, mentor engineers, and drive strategy for scalable, secure systems involving LLMs, RAG pipelines, and agentic AI workflows.

The role requires deep experience in AI/ML, distributed architectures, and hands-on engineering. You will collaborate with product and business stakeholders to align technical strategy with roadmap and

Qualifications

• 12+ years of professional software engineering experience.
• Bachelor's or Master's in CS/Engineering or equivalent professional experience.
• Minimum 3+ years in a Principal Engineer, Staff Engineer, or Enterprise Architect role.
• Proven experience architecting and delivering large-scale AI/ML or data-intensive solutions.
• Strong experience designing and operating highly available, distributed enterprise systems.
• Hands-on experience with LLM applications, RAG systems, vector databases, prompts, fine-tuning, or agentic workflows.

Responsibilities

• Lead end-to-end architecture, design, development, and delivery of scalable, secure AI-powered solutions.
• Define and evolve technical architecture for LLM apps, RAG pipelines, agentic AI workflows, and ML platforms.
• Design and implement cloud-native distributed solutions on AWS/Azure/GCP.
• Drive scalability, availability, security, observability, and cost optimization best practices.
• Champion AI-assisted software development using tools like GitHub Copilot, Cursor, Claude Code, and agentic tools.
• Mentor senior engineers and lead architecture reviews and trade-off decisions.
• Define DevOps, SRE, and MLOps practices including CI/CD, IaC, monitoring.

Skills

AI/ML leadership

Distributed systems

Cloud architecture

Mentoring

Technical strategy

LLM applications

Education

Bachelor's or Master's in CS/Engineering

Tools

Kubernetes

Docker

AWS

Azure

GCP

Python/Java/Node.js/Go

CI/CD

Terraform

OpenAI APIs

LangChain

Job description

Job Summary:

One of our clients, a leading technology organization, is looking for an experienced Principal Engineer to provide technical leadership in designing, architecting, and delivering scalable, secure, and highly available AI-powered and cloud-native solutions.

The role requires a strong combination of software architecture, Generative AI/ML, cloud technologies, distributed systems, and hands‑on engineering expertise. The candidate will work closely with engineering, product, and business stakeholders to define technical strategy, drive architecture decisions, mentor senior engineers, and build next‑generation intelligent applications.

Key Responsibilities:

• Lead the end-to-end architecture, design, development, and delivery of scalable, secure, and highly available AI-powered solutions.
• Define and evolve technical architecture for LLM applications, RAG pipelines, agentic AI workflows, and AI/ML platforms.
• Design and implement distributed, cloud-native solutions using AWS, Azure, and/or GCP.
• Drive best practices around scalability, availability, fault tolerance, observability, security, and cost optimization.
• Champion AI-assisted software development using tools such as GitHub Copilot, Cursor, Claude Code, and other agentic coding tools.
• Evaluate and integrate open-source frameworks, libraries, and platforms to develop sustainable and vendor-agnostic solutions.
• Provide hands‑on technical leadership through coding, proof‑of‑concepts, prototypes, code reviews, and critical architectural decisions.
• Establish engineering standards covering security, performance, scalability, observability, accessibility, privacy, and responsible AI.
• Lead architecture reviews and provide guidance on technical trade‑offs, build‑vs‑buy decisions, and platform standardization.
• Define and guide DevOps, SRE, and MLOps practices including CI/CD, Infrastructure as Code, model deployment, monitoring, and continuous evaluation.
• Mentor and coach senior engineers, technical leads, and architects.
• Collaborate with engineering, product, and solutions teams to align technical strategy with business objectives and product roadmaps.
• Stay current with emerging technologies in Generative AI, LLMs, agentic systems, cloud computing, and applied ML.

Required Qualifications:

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field, or equivalent professional experience.
• 12+ years of professional software engineering experience.
• Minimum 3+ years of experience in a Principal Engineer, Staff Engineer, or Enterprise Architect role.
• Proven experience architecting and delivering large‑scale, production‑grade AI/ML or data‑intensive solutions.
• Strong experience designing and operating highly available, distributed enterprise systems.
• Hands‑on experience with LLM applications, RAG systems, vector databases, prompt engineering, fine‑tuning, or agentic workflows.

Technical Skills:

• Generative AI / LLM / AI/ML
• RAG and Vector Databases
• Agentic AI and AI Workflows
• Python, Java, Node.js, or Go
• AWS / Azure / GCP
• Cloud Architecture
• Microservices and Distributed Systems
• Event-Driven Architecture
• Kubernetes / Docker
• PyTorch / TensorFlow / scikit-learn
• Hugging Face
• LangChain / LlamaIndex
• OpenAI / Anthropic / AWS Bedrock APIs
• DevOps / SRE / MLOps
• CI/CD and Infrastructure as Code
• Terraform / CloudFormation
• Prometheus / Grafana / OpenTelemetry
• Secure Coding, IAM, Data Privacy, and Compliance

Leadership & Communication:

• Strong technical leadership and ability to influence across teams without direct reporting authority.
• Excellent written and verbal communication skills.
• Ability to explain complex technical concepts to technical and non-technical stakeholders.
• Strong mentoring and coaching capabilities.
• Experience working in agile, iterative, and customer‑centric development environments.

Preferred Qualifications:

• Experience building and deploying agentic AI, multi-agent systems, or tool‑using LLM applications in production.
• Experience with open‑source projects or hybrid‑source software portfolios.
• Experience with workflow orchestration tools such as Camunda, M8Flow, Airflow, or Temporal.
• Familiarity with government digital standards and compliance frameworks such as SOC 2, ISO 27001, GDPR, HIPAA, or FedRAMP.
• Knowledge of responsible AI, model governance, AI safety, bias evaluation, and LLM red‑teaming.
• Cloud architecture or AI engineering certifications are an added advantage.