Software Architect

About the role

We are looking for a technically strong software engineering leader to own software quality, architecture and integrated delivery across our India software organisation. Our robots depend on multiple software disciplines working together reliably. You will help shape technology strategy and organisational direction, and translate that into sound architectural decisions, strong engineering practices and dependable execution. This is a hands-on leadership role combining technical depth, people management and accountability for outcomes.

Location: Bengaluru, Karnataka,  Reports to: Chief Technology Officer · Experience: 10+ years

About Us

We are building robots to maintain, organise and reset common public and commercial spaces — offices, campuses, venues and other high-traffic facilities. We are building a hybrid end-to-end architecture where classical and modern methods work together for maximum reliability and robustness, with R&D in Bengaluru and Wellington, New Zealand.

What you will do

Technology direction and architecture: help shape technology strategy and drive architecture decisions across robot software, cloud services, data processing and model training infrastructure. Own system-level requirements — latency, compute and memory budgets, end-to-end reliability. Establish clear interfaces and component ownership, and resolve technical trade-offs across the stack.

Software quality, security and engineering practices: set and embed standards for code quality, testing, documentation, observability and secure development. Own the software security review and audit process across robot and cloud systems, working with specialists where needed. Build quality into everyday development through effective reviews, automated validation and measurable acceptance criteria.

Integrated software delivery: own delivery across teams, turning product priorities into realistic plans with clear commitments, dependencies and milestones. Resolve execution bottlenecks and hold teams accountable for working software and demonstrated robot behaviour.

Integration, resilience and release readiness: own integration and release readiness across robot software, cloud services, and data and training pipelines, including Kubernetes. Define and validate behaviour during connectivity loss, service degradation and component failures, including safe fallback, recovery and rollback. Establish reproducible builds and simulation, hardware-in-the-loop, on-robot and cloud testing.

Hands-on technical leadership: stay close to implementation through critical design and code work, complex debugging and direct involvement in the most consequential technical problems.

People and team development: lead and develop engineers and technical leads; build capability through hiring, coaching, clear performance expectations and stronger technical ownership.

Cross-team alignment: bring teams together around shared technical decisions and delivery outcomes, including teams outside your reporting line.

Experience

• At least 10 years in robotics or AI, including technical leadership roles
• Strong understanding of autonomy systems such as VLA/VLM models, SLAM, planning, perception and ML-based decision-making
• Python, C++, ROS, and ML stacks such as PyTorch or TensorFlow
• Experience with robotics, embedded systems, autonomous systems or comparable products where software interacts with physical hardware
• Practical experience improving automated testing, continuous integration, release processes and production reliability
• Evidence of delivering programmes spanning multiple teams, including teams outside your reporting line
• Experience architecting and operating cloud platforms, containerised workloads, and large-scale data processing or model training pipelines

What success looks like

• Teams deliver predictably against a shared plan, with clear ownership and fewer late integration surprises
• Architecture supports product goals and makes the software easier to extend, test and maintain
• Releases produce measurable improvements in robot behaviour and reliability
• Recurring failures, escaped defects and avoidable engineering rework decrease
• Engineers and technical leads grow in capability, ownership and execution independence

Job Responsibilities:

We are seeking a highly skilled and motivated Robotics Engineers with a strong focus

on ROS2 development to join our dynamic team. As a Robotics Engineer, you will be

responsible for designing, developing, and implementing advanced robotic systems and

applications using the Robot Operating System 2 (ROS2). You need to develop the

behavioral and control systems, including planning and navigation needed for

autonomous robots. This role requires a deep understanding of robotic software

architecture, proficiency in ROS2, and experience with hardware integration and real

time systems and expertise in URDF (Unified Robot Description Format).

Key Responsibilities :

Design and Development:

 Develop robust and scalable robotic applications using ROS2. Implement

software for various robotic systems, ensuring high performance and reliability.

 Hand-on with developing ROS2 nodes, Services/Clients, Publishers/Subscriber.

 Lead and develop path/motion planning algorithms that include route planning,

trajectory optimization, decision making, and open space planning. Good

understandings of Robot dynamics, kinematics and modeling.

System Integration :

 Integrate sensors, actuators, and other hardware components with robotic

systems. Ensure seamless communication between hardware and software

layers. Experienced on integration with perception sensors such as IMU, GPS,

Stereo Cameras, Lidar, Radar, and various other sensors.

URDF Modeling :

 Create and maintain accurate URDF models for robotic systems. Ensure models

accurately represent the physical configuration and kinematics of the robots.

Algorithm Implementation :

 Implement and optimize algorithms for perception, localization, mapping,

navigation, and control.

Simulation and Testing :

 Utilize simulation tools to test and validate robotic systems in virtual

environments like Gazebo, Rviz2 and Unity.

Perform rigorous testing in real-world scenarios to ensure system robustness.

Documentation : Create and maintain comprehensive documentation for system architecture,

design decisions, algorithms, and user guides.

Research and Development :

 Stay updated with the latest advancements in robotics and ROS2, and URDF.

Contribute to the continuous improvement of development processes and tools.

All candidates must have at least a Bachelor’s degree in a related field(Computer

Engineering, Electronics/Electrical Engineering, Electronics and Communication

Engineering, Robotics or similar).

Advanced degrees are a plus.

Pncpl Software Engineer

Position Responsibilities :

• Lead the architecture and development of AI-powered, distributed systems that meet enterprise-grade performance and security standards.
• Leverage AI tools for code generation, architectural design, and documentation to accelerate delivery and improve quality.
• Design, build, and maintain services using Java following clean-code and secure design principles.
• Develop agentic AI-based tools, domain-specific copilots, and developer productivity enhancements.
• Collaborate with cross-functional teams to define modular, scalable, and compliant architecture patterns.
• Conduct technical design reviews and produce detailed documentation, including system specifications, API docs, and architecture diagrams.
• Integrate AI solutions into CI/CD pipelines, ensuring observability, automated testing, and deployment standards are met.
• Implement robust monitoring and performance engineering practices to maintain high-quality deployments.
• Continuously evaluate emerging AI technologies and integrate them into development workflows for maximum impact.
• Champion best practices in security, automation, and performance optimization across the organization.

Qualifications :

• 6+ years in software engineering with backend development in Java.
• 3+ years with AI tools for development, prototyping, or documentation tasks.
• Experience with cloud-native development and containerized deployment (Docker, Kubernetes).
• Knowledge of AI integration patterns, vector stores, prompt engineering, and RAG pipelines.
• Ability to design software architecture using sequence diagrams, ERDs, data models, and threat models.
• Comfortable with Gen AI-first environments and working with remote Agile teams.

Preferred Qualifications

• Experience building AI copilots or developer tools using OpenAI/Claude SDKs, LangChain, or similar frameworks.
• Experience working in a fast-paced, AIDLC environment, with a strong understanding of CI/CD practices.
• Familiarity with GitHub Actions, Argo Workflows, Terraform, and monitoring/observability tools.
• Containerization and Orchestration: Proficiency in Docker and Kubernetes for containerization and orchestration.
• Cloud Platforms: Experience with cloud computing platforms such as AWS, Azure, or OCI Cloud.

Strong Lead AI Engineer Profile with agentic systems architecture expertise

2

Mandatory (Experience 1): Must have 6+ years of software or ML engineering, with at least recent 2+ years building and shipping production LLM or agentic AI systems

3

Mandatory (Tech skill 1): Must have hands-on proficiency with at least two agentic frameworks (LangGraph, LangChain, AutoGen, CrewAI), with experience debugging framework internals

4

Mandatory (Tech skill 2): Must have direct SDK experience with Anthropic Claude API (tool use, streaming), OpenAI Assistants API, or Vertex AI Agent Builder

5

Mandatory (Tech skill 3): Must have Python mastery — production-quality code, type annotations, unit and integration tests, packaging, and performance profiling

6

Mandatory (Tech skill 4): Must have RAG pipeline depth — embedding model selection, vector stores (Pinecone, Weaviate, pgvector), hybrid retrieval, RAGAS or custom evaluation harnesses

7

Mandatory (Tech skill 5): Must have cloud deployment experience with AWS, Azure, or GCP; Docker, Kubernetes, IaC basics (Terraform or CDK), and CI/CD pipelines

8

Mandatory (Tech skill 6): Must have agent observability experience — LangSmith, Helicone, or equivalent — with ability to diagnose latency, cost, and quality issues in production traces

9

Mandatory (Tech skill 8) : Must have owned full sub-system designs — agent topology, data flows, API contracts, failure handling — for a bounded scope, and built multi-agent graphs, tool orchestration, retrieval, and memory systems.

10

Mandatory (Tech skill 7): Must have track record of shipping 2+ agentic or ML systems to production — not just proof-of-concepts — with documented performance benchmarks

11

Mandatory (Communication): Must be able to write crisp component specifications and communicate architectural trade-offs to both engineers and non-technical stakeholders

Strong Lead AI Engineer Profile with agentic systems architecture expertise

2

Mandatory (Experience 1): Must have 6+ years of software or ML engineering, with at least recent 2+ years building and shipping production LLM or agentic AI systems

3

Mandatory (Tech skill 1): Must have hands-on proficiency with at least two agentic frameworks (LangGraph, LangChain, AutoGen, CrewAI), with experience debugging framework internals

4

Mandatory (Tech skill 2): Must have direct SDK experience with Anthropic Claude API (tool use, streaming), OpenAI Assistants API, or Vertex AI Agent Builder

5

Mandatory (Tech skill 3): Must have Python mastery — production-quality code, type annotations, unit and integration tests, packaging, and performance profiling

6

Mandatory (Tech skill 4): Must have RAG pipeline depth — embedding model selection, vector stores (Pinecone, Weaviate, pgvector), hybrid retrieval, RAGAS or custom evaluation harnesses

7

Mandatory (Tech skill 5): Must have cloud deployment experience with AWS, Azure, or GCP; Docker, Kubernetes, IaC basics (Terraform or CDK), and CI/CD pipelines

8

Mandatory (Tech skill 6): Must have agent observability experience — LangSmith, Helicone, or equivalent — with ability to diagnose latency, cost, and quality issues in production traces

9

Mandatory (Tech skill 8) : Must have owned full sub-system designs — agent topology, data flows, API contracts, failure handling — for a bounded scope, and built multi-agent graphs, tool orchestration, retrieval, and memory systems.

10

Mandatory (Tech skill 7): Must have track record of shipping 2+ agentic or ML systems to production — not just proof-of-concepts — with documented performance benchmarks

11

Mandatory (Communication): Must be able to write crisp component specifications and communicate architectural trade-offs to both engineers and non-technical stakeholders

12

Mandatory (Note 1) : Role is Hybrid, WFH flexibility as well upto 6 days a month

PRINCIPAL AI ENGINEER @ METADOME.AI

Company Description

Metadome.ai builds frontier AI models that transform text, drawings, and CAD into production-ready, interactive 3D experiences. The company advances a full generative pipeline—text-to-CAD, 2D-to-3D

reconstruction, CAD completion and harmonization, and real-time interactive rendering—engineered for the precision required in the physical world. Its technology currently powers the modernization of

OEM aftersales for more than 30 automotive and heavy-equipment manufacturers worldwide, delivering accurate, scalable, and fast 3D solutions. Metadome.ai’s platform enables shoppable 3D parts, step-by-step repair animations, and a headless API that feeds consistent 3D assets into commerce, dealer, training, and service systems. The broader mission is to allow anyone to move from an idea, drawing, or specification to a production-grade 3D model and beyond in seconds.

Role Description

As a Principal AI Engineer — Generative CAD & 3D, you will lead the design, development, and deployment of advanced AI models that convert text, 2D drawings, and CAD files into engineering-grade 3D content. You will architect end-to-end generative pipelines, including

text-to-CAD, 2D-to-3D reconstruction, CAD completion, and real-time rendering, collaborating closely with product, design, and engineering teams to ship robust production systems. Day-to-day, you will experiment with novel neural network architectures, optimize model performance on large-scale CAD datasets, write high-quality production code, and guide the integration of AI services into customer-facing platforms. You will mentor other engineers, establish best practices for AI development, and contribute to technical strategy and roadmap. This is a full-time, hybrid role based in Bengaluru, with a mix of on-site collaboration and work-from-home flexibility.

Qualifications

• Strong foundation in Computer Science and Software Development, including data structures, algorithms, system design, and production-grade coding in languages such as Python, C++, or similar.
• Deep expertise in Neural Networks and Pattern Recognition, with hands-on experience designing, training, and deploying modern deep learning architectures for complex, high-dimensional data.
• Experience with Natural Language Processing (NLP), including working with text encoders, multimodal models, and integrating language understanding into generative workflows.
• Advanced degree (Master’s or PhD) in Computer Science, Electrical Engineering, Applied Mathematics, or a related field, or equivalent practical experience in AI/ML research and engineering.
• Background in 3D geometry, CAD, computer graphics, or related domains, with familiarity in 3D representations, mesh processing, and rendering pipelines.

Position Overview

We are seeking a versatile Senior Full Stack & AI Agent Developer to architect, build, and

maintain end-to-end software solutions spanning web platforms, desktop applications, and

autonomous AI agents capable of interacting with and controlling these software systems.

The ideal candidate will bridge traditional engineering software with cutting-edge artificial

intelligence to automate data processing and enhance operational decision-making. While

not strictly required, a background or strong interest in the energy sector—specifically

drilling and completion operations—is highly desirable.

Key Responsibilities

• Full Stack Development: Design, develop, and deploy robust web applications and

native desktop software utilized by engineering and operational teams.

• AI Agent Engineering: Build, train, and integrate autonomous AI agents and LLM-

driven workflows capable of interpreting data, executing commands, and safely

controlling desktop and web-based software.

• Workflow Automation: Translate complex workflows into intuitive software features

and autonomous agent actions, minimizing manual data entry and operational

bottlenecks.

• Data Integration: Handle high-frequency data streams and integrate them seamlessly

into user interfaces and backend AI models.

• Architecture & Scalability: Ensure high performance, security, and scalability across

cloud infrastructure (AWS/Azure), local desktop environments, and potential edge

computing setups.

• Cross-Functional Collaboration: Work closely with domain experts and end-users to

translate field challenges into technical product requirements.

Required Qualifications & Experience

• Experience: Minimum of 5 years of professional software development experience,

with a proven track record of delivering production-ready web and desktop

applications.

• Programming Languages: Strong proficiency in Python, JavaScript/TypeScript, and at

least one compiled language (C#, C++, or Java).• Web & Desktop Frameworks: Hands-on experience with modern frontend

frameworks (React, Angular, or Vue.js), Node.js, and desktop application development

(Electron, WPF, Qt, or Tauri).

• AI & Agent Tooling: Demonstrated experience building AI agents using LLM APIs

(OpenAI, Anthropic), open-source models (Hugging Face), LangChain, LlamaIndex,

AutoGPT, or custom agent architectures.

• Automation & UI Control: Expertise in software control mechanisms using tools like

Selenium, Playwright, PyAutoGUI, Appium, or computer vision-based GUI automation to

allow AI agents to navigate software.

• Cloud, DevOps & Databases: Experience with Git, Docker, CI/CD pipelines, cloud

platforms (AWS/Azure/GCP), RESTful APIs, GraphQL, and relational/NoSQL databases.

Preferred Qualifications (Strong Plus)

• Industry Domain Expertise: Prior hands-on development experience within the oil and

gas sector, specifically focused on drilling, completions, rig operations, or subsurface

engineering software.

• Data & Protocols: Familiarity with oilfield data standards (e.g., WITSML, OPC-UA) and

time-series databases.

• Experience deploying AI models and agents in edge or low-connectivity environments

(such as offshore rigs or remote drilling sites).

• Familiarity with safety-critical software design and cybersecurity standards in

industrial control systems (ICS/SCADA).

• Degree in Computer Science, Software Engineering, Petroleum Engineering, or a related technical discipline.

Role & Responsibilities

• Own end-to-end architecture, system design, development, and production deployment of scalable, AI-powered applications.
• Architect and develop high-performance backend services using Node.js, NestJS, TypeScript, Express.js, and Go.
• Design scalable web applications using React.js and Next.js, and cross-platform mobile applications using Flutter and Dart.
• Design distributed systems, microservices, event-driven architectures, and real-time applications capable of handling massive data volumes and high concurrent traffic.
• Design and optimize PostgreSQL/MySQL databases, MongoDB, Redis caching, database indexing, transactions, and query performance.
• Build real-time ride-booking, driver-allocation, location-tracking, and proximity-based matching systems using geospatial technologies such as PostGIS.
• Design and implement REST APIs, WebSockets, secure authentication, authorization, RBAC, and third-party integrations.
• Build and integrate Generative AI applications, LLM-powered chatbots, AI agents, RAG pipelines, embeddings, vector databases, tool calling, and intelligent automation workflows.
• Develop AI and backend services using Python and integrate LLM platforms such as OpenAI, Claude, and Gemini.
• Architect secure payment integrations, transaction workflows, webhook processing, idempotency, and payment reconciliation.
• Design and implement cloud-native infrastructure using AWS, Docker, CI/CD pipelines, and production monitoring tools.
• Ensure application security, scalability, reliability, performance, maintainability, and cost efficiency.
• Lead technical decision-making, code reviews, debugging, performance optimization, documentation, and mentoring of developers.
• Independently own critical engineering deliverables and drive products from concept and architecture through development, testing, deployment, and production support.

Preferred Candidate Profile

• 710+ years of software development experience, with substantial hands-on experience in technical architecture and production-grade application development.
• Expert-level proficiency in Node.js, NestJS, TypeScript, REST APIs, backend architecture, and microservices.
• Strong experience with React.js, Next.js, and modern frontend architecture.
• Hands-on experience with Flutter and Dart for Android and iOS application development.
• Proven experience designing scalable systems, handling large data volumes, concurrent workloads, and performance-critical applications.
• Strong experience with PostgreSQL, database design, indexing, query optimization, transactions, Redis, and geospatial systems.
• Practical experience building and deploying LLM-powered applications, AI agents, RAG systems, embeddings, vector search, and AI workflow automation.
• Proficiency in Python for AI integrations and backend services; Go language experience is highly desirable.
• Strong understanding of authentication, authorization, application security, payment integrations, and secure API design.
• Hands-on experience with AWS, Docker, CI/CD, Git, production deployments, logging, and monitoring.
• Familiarity with Kafka/RabbitMQ, Kubernetes, LangChain/LlamaIndex, and event-driven architectures is an advantage.
• Exceptional system-design, analytical, debugging, and problem-solving skills.
• Strong ownership, independent execution, technical leadership, communication, and mentoring abilities.
• Experience in startups or building products from scratch is highly desirable.

What We Expect

We are looking for a highly hands-on technical leader who can independently architect, design, develop, optimize, and deploy complex production systems. The ideal candidate must demonstrate genuine technical depth, strong engineering judgment, and the ability to lead end-to-end product development across backend, web, mobile, cloud, and AI technologies.

AI Architect – Enterprise AI & Generative AI ( Remote) - Contractual

Experience: 8+ years

Location: Remote, India

Employment Type: Contractual

Working Hours: 3:00 PM – 12:00 AM IST

Client Engagement: US-based client

About the Role

We are looking for a hands-on, client-facing AI Architect to lead the architecture, technical direction, and production implementation of enterprise AI and Generative AI solutions for a US-based client.

You should combine strong software engineering and cloud architecture fundamentals with practical experience building secure, scalable, and reliable AI applications. This role involves end-to-end technical ownership, from solution design and prototyping to production deployment and optimization. It is not a research-only, advisory-only, or prompt-writing position.

Key Responsibilities

• Lead end-to-end architecture and delivery of AI/ML and Generative AI solutions, from discovery and proof of concept to production rollout.
• Design LLM-powered applications using Retrieval-Augmented Generation (RAG), embeddings, vector databases, AI agents, and orchestration frameworks.
• Define data ingestion, chunking, retrieval, grounding, evaluation, and knowledge-refresh strategies.
• Select appropriate AI models and platforms based on quality, latency, cost, security, and operational requirements.
• Design cloud-native architectures, APIs, integrations, identity controls, monitoring, and resilient deployment patterns.
• Create architecture diagrams, technical designs, implementation roadmaps, and technical standards.
• Implement AI quality and safety measures, including hallucination mitigation, guardrails, access controls, and prompt-injection defenses.
• Guide engineering, data, ML, and DevOps teams through implementation, code reviews, troubleshooting, and go-live readiness.
• Lead technical discussions and design reviews with US client stakeholders.
• Establish production monitoring, CI/CD, versioning, incident handling, and performance and cost optimization practices.

Required Skills & Qualifications

• 8+ years of relevant experience in software engineering, AI/ML engineering, data engineering, or technology architecture.
• Proven experience personally architecting and deploying at least one enterprise-grade AI or Generative AI solution into production.
• Strong practical knowledge of LLMs, RAG, embeddings, vector databases, orchestration frameworks, and model evaluation.
• Hands-on experience with Python and APIs, including prototyping, code review, and troubleshooting.
• Experience with at least one major cloud platform: Microsoft Azure, AWS, or Google Cloud Platform (GCP).
• Understanding of data pipelines, SQL/NoSQL databases, containers, CI/CD, MLOps, and LLMOps.
• Knowledge of enterprise security, privacy, identity and access management, and responsible AI practices.
• Experience independently leading architecture workshops, design reviews, and technical discussions with US clients.
• Excellent written and spoken English, documentation, and stakeholder management skills.
• Availability to work from 3:00 PM to 12:00 AM IST and willingness to accept a contractual engagement.

Preferred Experience

• Azure AI Foundry, Azure OpenAI, Amazon Bedrock, or Google Vertex AI.
• Azure AI Search or equivalent retrieval tools.
• LangChain, LangGraph, Semantic Kernel, and agent/tool orchestration.
• Model fine-tuning, predictive ML, document intelligence, multimodal AI, or real-time AI applications.
• Experience in cloud modernization, enterprise integrations, data analytics, or technology consulting.
• Relevant AI/cloud architecture certifications and experience mentoring technical teams.

What Success Looks Like

• Designing secure, scalable, production-ready AI solutions rather than demos or conceptual presentations.
• Making sound technical decisions around feasibility, performance, reliability, cost, and AI risks.
• Taking ownership of architecture decisions and resolving technical blockers with limited supervision.
• Building trust with senior US stakeholders and collaborating effectively with India-based delivery teams.

Contract Details

• Initial engagement: Minimum 3 months, with extension subject to project requirements and performance.
• Working schedule: 3:00 PM – 12:00 AM IST.
• Potential permanent employment: After 18 months, the client may consider direct permanent employment at its sole discretion. Conversion is not guaranteed.

Mandatory Screening Criteria

Candidates should be able to:

• Explain an enterprise AI/GenAI solution they personally architected and deployed, including architecture, scale, evaluation, and business impact.
• Whiteboard an enterprise RAG or agentic solution covering data flow, security, authentication, authorization, monitoring, and cost controls.
• Discuss real-world model-quality issues, hallucinations, privacy risks, incidents, and architectural trade-offs.
• Lead a technical design review with US client stakeholders.
• Confirm acceptance of the working hours and contractual engagement.

Apply only if you have hands-on experience architecting and deploying enterprise AI/GenAI solutions in production.

Looking for an Architect with strong experience in AI and Data Engineering, preferably with hands-on experience in Generative AI (GenAI). Candidates with experience in any cloud platform (AWS, Azure, or GCP) will be considered,