Principal Scientist - AI Research

Technoworkz Technologies; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Technoworkz Technologies seeks an AI Systems Architect to own end-to-end design and delivery of production-grade agentic and Generative AI systems on AWS. This hands-on role demands deep architectural insight, coding proficiency, and focus on performance, scalability, and reliability.

You will guide developers, architect secure, cost-efficient platforms, and ensure observability, governance, and production readiness across GenAI pipelines, RAG workflows, and evaluation frameworks.

Qualifications

• Education from a top-tier institute (IIT/Tier-1) in CS/AI or related field.
• 7–10 years in software/AI engineering with 4+ years GenAI app development and 2+ years architecting agentic AI systems.
• Expert in Python 3.11+ (asyncio, typing, packaging, profiling, pytest).
• Hands-on experience with Semantic Kernel, LangGraph, AutoGen, or CrewAI.

Responsibilities

• Architect robust production AI systems for agentic architecture, including planning, reasoning, tool-calling, GenAI/RAG pipelines, and evaluation workflows.
• Optimize throughput, latency, concurrency, autoscaling, and GPU sizing for cost-efficient deployments.
• Lead deep debugging, fix critical defects, and improve code quality with ML/MLOps stability practices.
• Build reference implementations using Semantic Kernel, LangGraph, AutoGen, or CrewAI with strong grounding and memory management.
• Set up observability with OpenTelemetry and Datadog; standardize dashboards and incident response.
• Govern testing and rollout frameworks with golden sets, A/B tests, and regression suites.
• Develop reusable SDKs, connectors, CI/CD templates, and architecture checklists.
• Collaborate cross-functionally with product, data, and SRE teams for capacity planning and DR strategies.
• Mentor engineers to strengthen design and reliability practices.

Skills

GenAI experience

Python proficiency

Leadership & mentoring

MLOps & stability

System design & debugging

Education

Bachelor’s/Master’s in CS/AI (IIT/Tier-1)

Tools

Semantic Kernel

LangGraph

AutoGen

CrewAI

Job description

As the AI Systems Architect, youll own the end-to-end design and delivery of

production-grade agentic and Generative AI systems. This is a highly hands-on role

requiring deep architectural insight, coding proficiency, and an obsession with

performance, scalability, and reliability. You’ll architect secure, cost-efficient AI

platforms on AWS, guide developers through complex debugging and optimization,

and ensure all systems are observable, governed, and production-ready.

Key Responsibilities

• Architect Production AI Systems: Design robust overall architectures for agentic systems (planning, reasoning, tool-calling), GenAI/RAG pipelines, and evaluation workflows. Create detailed design documents including flow/UML/sequence diagrams and AWS deployment topologies. Additionally, ensure architectures support advanced LLM training and inference workflows, incorporating distributed strategies for scalability.
• Optimize for Cost & Performance: Model throughput, latency, concurrency, autoscaling, CPU/GPU sizing, and vector index performance to ensure scalable, efficient deployments. Include optimization for multi-node GPU clusters and distributed training efficiency to reduce compute overhead.
• Lead Debugging & Stability Efforts: Conduct deep-dive debugging, fix critical defects, and resolve production incidents; pair-program with developers to improve code quality and performance. Apply MLOps-driven stability practices, leveraging configuration management and automated recovery for high availability.
• Standardize Agentic Frameworks: Build reference implementations using Semantic Kernel (preferred), LangGraph, AutoGen, or CrewAI with strong schema validation, grounding, and memory management.
• Implement Observability & Monitoring: Set up distributed tracing, metrics, and logging via OpenTelemetry and Datadog. Standardize dashboards, alerts, and incident response workflows.
• Govern Evaluation & Rollouts: Build test and evaluation frameworks—golden sets, A/B experiments, regression suites, and controlled rollouts—to ensure consistent quality across releases.
• Establish Engineering Standards: Create reusable SDKs, connectors, CI/CD templates, and architecture review checklists to promote consistency across teams.
• Cross-Functional Leadership: Collaborate with product, data, and SRE teams for capacity planning, DR strategies, and post-incident RCA reviews.
• Mentor engineers to strengthen design and reliability practices

Required Qualifications

• Education: Bachelor’s/Master’s from a top-tier institute (IIT/Tier-1) in Computer Science, AI, or related field.
• 7–10 years in software/AI engineering, including 4+ years in GenAI application development and 2+ years architecting agentic AI systems.
• Expert in Python 3.11+ (asyncio, typing, packaging, profiling, pytest).
• Hands-on experience with Semantic Kernel, LangGraph, AutoGen, or CrewAI.
• Proven delivery of GenAI/RAG systems on AWS Bedrock or equivalent vector-based platforms (OpenSearch Serverless, Pinecone, Redis).
• Deep understanding of AWS ecosystem: EKS, Bedrock, S3, SQS/SNS, RDS, ElastiCache, Secrets Manager, IAM/Okta, Kong API Gateway