Senior Technical Manager

Job Description: Tech Lead – AI & Technology

Role Title: Tech Lead – AI & Technology

Location: Bangalore, India – Fully On-site

Experience: 5+ Years

Employment Type: Full-time

About the Role

We are looking for an experienced and hands-on Tech Lead to lead a small engineering team and drive the development of AI-powered applications, internal technology platforms, and modern IT solutions. The Tech Lead will be responsible for technical direction, architecture, development, code quality, team management, and end-to-end delivery of technology projects. The ideal candidate should have strong programming experience, particularly in Python and ReactJS, along with practical experience working with AI/ML technologies.

1. Technical Leadership & Team Management

• Lead and mentor a team of developers and technical team members.
• Own technical delivery across multiple projects and initiatives.
• Assign tasks, review progress, resolve technical blockers, and ensure timely delivery.
• Conduct code reviews and establish engineering best practices.
• Mentor team members and support their technical growth.

2. Software Development & Architecture

• Design and develop scalable, secure, and maintainable applications.
• Lead backend development using Python and frontend development using ReactJS.
• Define application architecture, technology choices, APIs, integrations, and development standards.
• Review technical designs and ensure high-quality implementation.
• Troubleshoot complex technical issues and drive effective solutions.

3. AI & Technology

• Lead the development and integration of AI-powered applications and solutions.
• Work with AI/ML models, APIs, LLMs, Generative AI, and related technologies.
• Evaluate emerging AI tools and technologies and identify opportunities for practical implementation.
• Collaborate with product and business teams to translate requirements into AI-enabled technology solutions.

4. Project Delivery

• Own the complete technology lifecycle from requirements and architecture to development, testing, deployment, and maintenance.
• Plan sprints, estimate development efforts, and track technical milestones.
• Work closely with cross-functional stakeholders to understand requirements and deliver solutions.
• Ensure projects meet timelines, quality standards, security requirements, and performance expectations.

5. Engineering Quality & Infrastructure

• Establish standards for coding, testing, documentation, version control, and deployment.
• Ensure applications are scalable, reliable, and secure. l Collaborate on cloud infrastructure, APIs, databases, CI/CD, and deployment processes.
• Identify opportunities to improve system performance and engineering efficiency.

Technical Skills – Must Have

• 5+ years of software development experience.
• Strong hands-on experience with Python.
• Strong experience with ReactJS / React.
• Experience leading or managing technical team members.
• Strong understanding of AI/ML and Generative AI technologies.
• Experience with APIs, databases, Git, and software development lifecycle.
• Strong understanding of application architecture and system design.
• Experience building and deploying production-grade applications.

Technical Skills – Good to Have

• Experience with LLMs, RAG, AI agents, or Generative AI applications.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Experience with Docker, CI/CD, and DevOps practices.
• Experience integrating third-party AI APIs and services.
• Experience working in startups or fast-paced technology environments.

What We Are Looking For

• Strong technical ownership and problem-solving ability.
• Ability to balance hands-on coding with team leadership.
• Excellent communication and stakeholder management skills.
• Ability to mentor developers and drive accountability within the team
• Strong interest in AI and emerging technologies.
• A proactive, ownership-driven approach with the ability to work in a fast-paced environment.

Why Join Us?

• Work on AI-powered technology with meaningful social impact.
• Lead a small, high-ownership technology team.
• Work across AI, software engineering, and modern IT infrastructure.
• Opportunity to shape technology architecture and engineering practices from the ground up.
• Collaborative and fast-moving environment with significant technical ownership.

Role & Responsibilities

Responsibilities

• Business: Immerse in operations until you think like an insider.

Rapidly acquire domain expertise through direct observation, translate between business and engineering seamlessly, and mentor engineers in your area on immersion. Influence senior stakeholders effectively, manage complex stakeholder landscapes with competing agendas, and build trust rapidly with new stakeholders.

• Delivery: Lead rapid delivery initiatives across teams in your area, coach on prototype-first approaches, and establish trust through consistent fast delivery. Build complete applications rapidly across any technology stack, select the right tools for each problem, and define clear criteria for prototype-to-production transitions.

• Generative AI: Architect RAG systems for complex use cases across teams, implement advanced techniques (hybrid search, reranking, query expansion), mentor engineers on RAG best practices, and establish RAG standards. Lead evaluation strategy across teams, establishing annotation guidelines, training human-calibrated LLM judges, and building evaluation pipelines that connect tracing to datasets to experiments.

• People: Build high-performing teams across your area, navigate complex interpersonal dynamics, foster psychological safety, and create environments where diverse perspectives are valued. Influence through communication at all levels — from frontline to executive. Handle difficult conversations skilfully and train engineers in your area on effective communication.

• AI-Augmented Development: Optimise AI tool usage across teams in your area, train engineers on AI-augmented and agentic engineering workflows, evaluate new AI development tools, and establish practices that balance AI speed with verification rigour.

• Scale: Design complex multi-component systems end-to-end, evaluate architectural options for large initiatives across teams, guide technical decisions for your area, and mentor engineers on architecture. Create debt reduction strategies across teams, influence roadmap decisions to include debt work, and teach engineers when to accept debt for speed versus when to invest in quality.

• Documentation: Define documentation standards across teams in your area, create documentation systems and templates, train engineers on spec-driven development, and ensure documentation quality across projects. Lead pattern generalization initiatives, defining criteria for when to generalize versus keep custom.

• Reliability: Define reliability standards across teams in your area, drive post-incident improvements systematically, design capacity planning processes, andmentor engineers on SRE practices.

Ideal Candidate

• Strong Staff Software Engineer / FDE profile (full-stack + production GenAI, multi-team technical leadership)
• Mandatory (Experience 1) – Must have 7+ years of relevant professional software engineering experience, with demonstrated full-stack delivery across backend and frontend.
• Mandatory (Experience 2) – Must have deep production experience with Python AND JavaScript/TypeScript, working comfortably across the full stack.
• Mandatory (Experience 3) – Must have 2+ years of experience in generative AI applications developement — LLM integrations, vector databases, RAG systems, and evaluation pipelines
• Mandatory (Experience 4) – Must have strong experience with modern frontend frameworks (Next.js / React) and backend API development.
• Mandatory (Experience 5) – Must have extensive experience with cloud platforms (AWS preferred; Azure/GCP valued), including infrastructure-as-code (CloudFormation / Terraform).
• Mandatory (Experience 6) – Must have working knowledge of multiple database paradigms — relational (PostgreSQL), document, and key-value (Redis) — with ability to select the right storage per problem.
• Mandatory (Experience 7) – Must have strong experience with CI/CD pipelines (e.g. GitHub Actions), containerization, and production deployment strategies.
• Mandatory (Experience 8) – Must have demonstrable fluency with AI coding tools (Claude Code, Cursor, GitHub Copilot, or similar) and proven ability to design agentic engineering workflows and train teams on them
• Preferred (Experience) – Advanced RAG techniques — hybrid search, reranking, query expansion — and establishing RAG standards across teams

• Business: Immerse in operations until you think like an insider.Rapidly acquire domain expertise through direct observation, translate between business and engineering seamlessly, and mentor engineers in your area on immersion. Influence senior stakeholders effectively, manage complex stakeholder landscapes with competing agendas, and build trust rapidly with new stakeholders.
• Delivery: Lead rapid delivery initiatives across teams in your area, coach on prototype-first approaches, and establish trust through consistent fast delivery. Build complete applications rapidly across any technology stack, select the right tools for each problem, and define clear criteria for prototype-to-production transitions.
• Generative AI: Architect RAG systems for complex use cases across teams, implement advanced techniques (hybrid search, reranking, query expansion), mentor engineers on RAG best practices, and establish RAG standards. Lead evaluation strategy across teams, establishing annotation guidelines, training human-calibrated LLM judges, and building evaluation pipelines that connect tracing to datasets to experiments.
• People: Build high-performing teams across your area, navigate complex interpersonal dynamics, foster psychological safety, and create environments where diverse perspectives are valued. Influence through communication at all levels — from frontline to executive. Handle difficult conversations skilfully and train engineers in your area on effective communication.
• AI-Augmented Development: Optimise AI tool usage across teams in your area, train engineers on AI-augmented and agentic engineering workflows, evaluate new AI development tools, and establish practices that balance AI speed with verification rigour.
• Scale:  Design  complex  multi-component systems  end-to-end,  evaluate architectural options for large initiatives across teams, guide technical decisions or your area, and mentor engineers on architecture. Create debt reduction strategies across teams, influence roadmap decisions to include debt work, and teach engineers when to accept debt for speed versus when to invest in quality.

What You Bring

• Bachelor’s degree in computer science, Software Engineering, or related field with 7+ years of relevant professional experience.
• Deep production experience with Python and JavaScript/TypeScript across backend and frontend, with demonstrated ability to work comfortably across the full stack.
• Strong experience with modern frontend frameworks (such as Next.js or React) and backend API development.
• Extensive experience with cloud platforms (AWS preferred; Azure or GCP also valued), including infrastructure-as-code tools (such as CloudFormation or Terraform).
• Deep Working knowledge of multiple database paradigms, including relational databases (such as PostgreSQL), document databases, and key-value stores (such as Redis), with the ability to select the right storage technology for each problem.
• Strong experience with CI/CD pipelines (such as GitHub Actions), containerisation, and production deployment strategies.
• Demonstrable fluency with AI coding tools (such as Claude Code, Cursor, GitHub Copilot, or similar) and proven ability to design agentic engineering workflows and train teams on AI-augmented development practices.
• Hands-on experience architecting production generative AI applications (LLM integrations, vector databases, RAG systems, evaluation pipelines) is essential.
• Experience leading technical initiatives across multiple teams, mentoring engineers, and establishing engineering practices is required.
• Experience navigating ambiguous problem spaces, working directly with business stakeholders and end users, and shipping working solutions rapidly is required.
• Experience in an embedded, forward-deployed, or consulting-style engineering model is a strong plus.

• Must have exceptional communication skills and demonstrated ability to influence at senior levels. This role requires comfort leading across ambiguous environments, building trust-based relationships with commercial stakeholders at all levels, developing junior and mid-level engineers, and making strategic decisions that balance delivery speed with architectural integrity. You will shape engineering practices across your area and be expected to lead multi-team initiatives.

Technical Architect – Product Engineering

Experience: 15+ Years

Location: Pune, India

Employment Type: Full-time

Desired Skills: Python, Technical Architecture, AWS, Microservices, SaaS / Multi-tenant Architecture, Kubernetes, System Design

About the Role

We are looking for a Senior Technical Architect to lead the architecture, design, and technical evolution of an enterprise SaaS product. This is a hands-on leadership role requiring deep technical expertise, strong product engineering experience, and the ability to build scalable, secure, and high-performance platforms.

The ideal candidate should be passionate about solving complex engineering problems, driving innovation, mentoring development teams, and effectively leveraging AI to accelerate software development.

Key Responsibilities

• Own the overall product architecture and technical roadmap.
• Design and build scalable, secure, and highly available enterprise applications.
• Lead the design and implementation of new product features from concept to production.
• Remain hands-on with coding and contribute to critical product components.
• Drive architecture reviews, code quality, performance optimization, and engineering best practices.
• Lead cloud architecture, security, scalability, and DevOps initiatives.
• Evaluate and adopt modern technologies to improve product capabilities and engineering efficiency.
• Leverage AI tools (ChatGPT, GitHub Copilot, Cursor, Claude, etc.) to accelerate software development, code reviews, testing, documentation, debugging, and productivity.

Required Skills & Qualifications

• 15+ years of software product engineering experience with at least 5 years in a Technical Architect role.
• Strong hands-on expertise in Python and modern backend frameworks.
• Deep experience with AWS services and cloud-native application architecture.
• Strong understanding of DevOps, CI/CD pipelines, Infrastructure as Code (Terraform/CloudFormation), Docker, Kubernetes, and container orchestration.
• Experience designing microservices, REST APIs, event-driven architectures, and distributed systems.
• Strong knowledge of SQL and NoSQL databases.
• Experience with scalable SaaS platforms, multi-tenant architectures, and secure application design.
• Excellent understanding of software design patterns, performance tuning, observability, and system reliability.
• Strong analytical, problem-solving, and decision-making skills.

About Us

We believe the future of software development is AI-native — where engineers operate at a higher level of abstraction and quality remains non-negotiable. 

Incubyte is a software craft consultancy where the “how” of building software matters as much as the “what”.  

We partner with companies of all sizes, from helping enterprises build, scale, and modernize to early-stage founders bring their ideas to life. 

Our engineers operate in an AI-native development model, using AI as a collaborator across the SDLC to accelerate development while upholding the discipline of software craftsmanship. Guided by Software Craftsmanship and Extreme Programming practices, we build reliable, maintainable, and scalable systems with speed, without compromising quality. If this way of building software resonates with you, we’d like to talk. 

Our Guiding Principles 

These principles define how we work at Incubyte. They are non-negotiable. 

Relentless Pursuit of Quality with Pragmatism 

  We build high-quality systems without losing sight of delivery. 

Extreme Ownership 

  We take responsibility end-to-end for decisions, execution, and outcomes. 

Proactive Collaboration 

  We collaborate closely, challenge each other, and solve problems together. 

Active Pursuit of Mastery 

  We continuously improve our craft and raise our bar. 

Invite, Give, and Act on Feedback 

We seek, give, and act on feedback to get better every day. 

Ensuring Client Success 

We act as trusted partners and focus on real outcomes, not just output. 

Experience Level

This role is ideal for engineers with total 3+ years of experience with a proven track record of shipping complex projects successfully.

An experienced individual contributor and leader who thrives in large, complex projects with widespread impact.

What You’ll Do as a Software Craftsperson 

• Design and build high-quality, maintainable systems using disciplined engineering practices such as TDD, continuous refactoring, and pair programming 
• Operate in an AI-native development model, using AI as a collaborator to explore architecture and design, accelerate development, and continuously improve systems while applying strong judgment to ensure that speed never compromises quality 
• Take end-to-end ownership of outcomes from problem understanding and system design to implementation, deployment, and operation in production 
• Make thoughtful design decisions that balance simplicity, scalability, and long-term maintainability in real-world systems 
• Maintain a high bar for engineering quality through rigorous testing, code reviews, and continuous feedback 
• Investigate and resolve production issues, and implement systemic improvements to prevent recurrence 
• Work directly with clients, navigate ambiguity, and translate business problems into well-designed technical solutions 
• Contribute to improving team practices, tooling, and systems to raise the overall quality and effectiveness of engineering 

Requirements

What You’ll Bring 

• 3+ years of experience building high-quality, production systems (flexible based on demonstrated capability) 
• Strong fundamentals in software engineering, including object-oriented design, system design, and testing practices such as TDD 
• Demonstrated ability to build simple, maintainable, and scalable systems with a focus on long-term reliability 
• Proficiency in one or more modern technologies, Python, PHP, JavaScript, or TypeScript, with the ability to learn new technologies quickly 
• Deep experience working with Git in collaborative environments, including managing shared codebases, conducting code reviews, and maintaining a high bar for quality 
• Ability to operate effectively in an AI-native workflow using AI as a collaborator to explore solutions and accelerate development, while applying strong judgment to ensure correctness, quality, and maintainability 
• Clear thinking and strong problem-solving ability, with the capacity to break down complex problems into simple, well-structured solutions 
• A strong sense of ownership — you take responsibility for outcomes, care deeply about quality, and are not comfortable shipping work that does not meet your standards.

Benefits

Life at Incubyte 

We are a remote-first company with structured flexibility. Teams commit to shared rhythms during core hours, ensuring smooth collaboration while maintaining autonomy. Twice a year, we come together in person for a co-working sprint and once a year for a retreat - with all travel expenses covered. 

Our environment is built for crafters: pairing, refactoring, experimenting with AI, and pushing the boundaries of software excellence. We are all lifelong learners, and our work is our passion. 

Perks

• Dedicated learning & development budget. 
• Sponsorship for conference talks. 
• Comprehensive medical & term insurance. 
• Employee-friendly leave policies. 
• Home Office fund 
• Medical Insurance

Dear Candidate,

We have an immediate opening with Mphasis for Senior Full Stack Engineer (Python AI).

📍 Location: Hyderabad / Bangalore

💼 Experience: 5+ Years

🏢 Employment: Permanent

⚡ Immediate Joiners Preferred

Mandatory Skills:

• Python
• Java + Spring Boot
• React.js
• MongoDB

GenAI

Chief Engineer - Artificial Intelligence

AI Architecture | Production Engineering | LLM, RAG & Agentic AI

Primary objective: Build secure, scalable and reusable AI capabilities that move from experimentation to reliable production use across DocTutorials products and business functions.

Department

Technology & Product Engineering

Location

Hyderabad / Chennai

Reports to

Vice President - Technology

Experience

10+ years in software engineering, including 5+ years in AI/ML

Role Summary

The Chief Engineer - AI will define and lead AI engineering architecture, standards and production implementation. This is a senior, hands-on technical leadership role responsible for building reliable AI platforms and guiding AI engineers, data teams and application teams.

Key Responsibilities

1. AI Strategy and Architecture

·       Define the AI engineering strategy, architecture and technical roadmap.

·       Evaluate and select suitable models, frameworks, vector databases and AI platforms.

·       Make practical build-versus-buy and open-source-versus-commercial decisions.

·       Ensure AI solutions are modular, reusable, scalable, secure and cost-effective.

2. Production AI Engineering

·       Lead AI initiatives from use-case assessment and proof of concept through production deployment.

·       Build reusable AI services, APIs, pipelines and platform components for web, mobile and internal applications.

·       Establish development, testing, deployment, monitoring and production-support practices.

·       Resolve complex issues involving model quality, retrieval, performance, reliability and cost.

3. LLM, RAG and Agentic AI

·       Design LLM applications, enterprise RAG solutions and controlled AI-agent workflows.

·       Build document processing, chunking, embedding, indexing, retrieval and response pipelines.

·       Implement source traceability, human approval and clear permissions for sensitive use cases.

·       Improve response quality through prompt design, retrieval optimisation and evaluation.

4. AI Quality, Security and Responsible AI

·       Define evaluation standards for accuracy, relevance, groundedness, safety, latency and cost.

·       Introduce benchmark datasets and regression testing for prompts, models and retrieval pipelines.

·       Implement safeguards for hallucinations, unsupported responses, data leakage and unsafe actions.

·       Ensure role-based access, encryption, audit logging, secure secrets handling and approved data usage.

5. AI Platform and Integration

·       Create common AI capabilities and integration standards that can be reused across products and teams.

·       Integrate AI services with applications, databases and approved enterprise data sources.

·       Implement observability for model usage, quality, errors, response time and cost.

·       Reduce dependency on a single model provider, individual engineer or external vendor.

6. Technical Leadership and Team Development

·       Define AI engineering standards for architecture, coding, review, testing and documentation.

·       Remain hands-on through design reviews, critical code reviews, debugging and focused prototypes.

·       Mentor AI/ML engineers, data engineers and application teams; support hiring and capability building.

·       Work with Product and business teams to convert high-value problems into measurable AI solutions.

Required Skills and Experience

·       10+ years of software engineering experience, including 5+ years in practical AI/ML engineering.

·       Proven experience moving AI solutions from prototype to reliable production use.

·       Strong Python and production API development experience, preferably FastAPI.

·       Strong knowledge of LLMs, RAG, prompt engineering, embeddings and agentic AI.

·       Experience with vector databases such as pgvector, Qdrant, Milvus or Weaviate.

·       Experience with LangChain, LlamaIndex, Haystack or similar orchestration frameworks.

·       Knowledge of cloud architecture (preferably AWS), microservices, databases, queues and distributed systems.

·       Experience with Docker, Kubernetes, CI/CD, observability and production support.

·       Strong understanding of application security, data privacy and responsible-AI engineering.

·       Demonstrated technical leadership, mentoring and stakeholder-management capability.

Good-to-Have Experience

·       Healthcare, medical education, EdTech or digital-learning platforms.

·       Medical-content intelligence, knowledge graphs, ontologies, taxonomy or semantic search.

·       Clinical Case Library, personalised learning or recommendation systems.

·       Multi-modal AI involving text, audio, images or video.

·       Healthcare-data privacy, de-identification or standards such as SNOMED CT, ICD, HL7 or FHIR.

How Success Will Be Measured

·       Production adoption and measurable business or learner impact of AI capabilities.

·       Accuracy, groundedness, reliability, security and cost efficiency of AI solutions.

·       Reusable AI services delivered across products with reduced technical and vendor dependency.

·       Improved capability, engineering quality and ownership within the AI team.

We are looking for a hands-on AI engineering leader who can distinguish a valuable production capability from an attractive demo and build AI that is secure, scalable, measurable and maintainable.

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.

We are looking for a Senior Full Stack Engineer to join our lean, high-impact engineering team. This is a key founding-team role where you will work closely with the CTO and help build the engineering foundation of the company.

The ideal candidate is a backend-strong full-stack engineer with solid Python and React experience, a strong understanding of AI/LLMs, and the ability to independently take ownership of projects from idea to production.

What You'll Do:

• Build and scale applications across the backend and frontend
• Develop backend services and APIs using Python
• Build and maintain frontend applications using React
• Design and implement AI/LLM-powered applications and features
• Work with AI services and integrate them into real-world applications
• Contribute to system design and architecture
• Work with cloud infrastructure and services
• Take ownership of features and initiatives from ideation to production
• Identify problems and proactively drive solutions without requiring constant direction
• Work closely with the CTO and founding team to shape engineering practices and future systems
• Communicate technical concepts clearly to technical and non-technical stakeholders

What We're Looking For:

• 3–6 years of software engineering experience
• Strong experience with Python
• Good hands-on experience with React
• Strong backend development experience with full-stack exposure
• Practical understanding of AI, LLMs and AI services
• Experience building at least one meaningful AI project beyond basic API/chatbot integrations
• Experience taking an AI/ML application or feature into production is preferred
• Exposure to cloud platforms
• Good understanding of system design and software architecture
• Strong problem-solving and ownership mindset
• Excellent communication skills and ability to explain complex technical concepts in simple language
• Genuine hands-on experience with the technologies mentioned on the resume

What Makes This Role Different:

This is not a typical execution-focused engineering role. We are building a lean "A-team" of experienced engineers who will eventually help shape the team and take on senior/leadership responsibilities.

We're looking for someone who:

• Takes initiative rather than waiting for tasks
• Can work independently in an early-stage environment
• Is comfortable exploring and building with AI
• Can go deep into the work they've done and explain the technical decisions behind it
• Wants significant ownership and influence over the product and engineering direction

Location & Compensation

• Work Mode: Remote initially
• Future Location: Expected relocation to Bangalore in approximately 1 year
• Working Hours: Regular IST hours
• Travel: Potential opportunities to travel to Germany

Interview Process:

3 Rounds

1. Technical & Project Deep Dive – Conversational discussion around past projects, AI experience and technical depth
2. System Design & Technical Round – Deeper technical and architecture discussion
3. Founder Round – Communication, culture fit, ownership and initiative

Required Experience: 10–15 years (with at least 3–5 years in leadership roles)

● 10–15 years of overall experience in backend engineering, with strong exposure to

Python and/or Golang.

● 3–5 years of experience managing engineering teams.

● Proven experience delivering large-scale, distributed systems in production

environments.

● Strong understanding of microservices, cloud-native architecture, and DevOps

practices.

● Hands-on background in backend engineering (able to guide teams technically, even

if not coding daily).

● Familiarity with CI/CD pipelines, observability, and performance optimization.

● Experience in financial services or high-transaction domains is a plus.

● Experience leading teams that have utilized AI-driven development practices (e.g.,

agentic coding, LLM integration) to improve productivity and innovation is a

significant advantage.

Skills

● Excellent leadership and people management abilities.

● Strong communication and stakeholder management skills.

● Ability to balance technical depth with business priorities.

● Problem-solving mindset with a focus on delivery and impact.

● Passion for building engineering culture and improving developer experience.