POD Lead - AI & ML at Ampera Technologies · Remote only · 10 - 15 years · Profitable · Remote only · Posted 30 Jun 2026

Role Overview
We are seeking a hands-on technology POD Lead who blends engineering excellence with statistical rigor and business acumen to drive end-to-end product delivery in an agile, data-driven environment. The ideal candidate will lead a multidisciplinary team of BI developers, data engineers, ML practitioners, and product analysts to accelerate business growth through scalable, AI-enabled products, econometric models and intelligent insights.
This role sits at the intersection of engineering, analytics, econometrics, MLOps and growth strategy, requiring a balance of technical depth, stakeholder engagement, and agile execution.
Key Responsibilities
1. Leadership & Delivery
- Lead a cross-functional pod of data engineers, BI developers, statisticians and machine learning engineers to deliver AI-powered products and analytics solutions.
- Translate strategic goals into data science roadmaps executed in agile sprints, ensuring measurable business outcomes for every release.
- Foster a culture of experimentation, accountability, and rapid iteration across data, AI, and product workstreams.
2. Product & Business Integration
- Partner with business stakeholders across Sales, Marketing, Finance, and Operations to identify high-impact use cases such as churn prediction, growth forecasting, pricing optimization, causal impact analysis or next-best-action recommendations.
- Drive the roadmap for analytical and econometric product capabilities (e.g., predictive dashboards, personalization engines, time-series forecasting, and more).
- Ensure all solutions are aligned with enterprise data strategy, governance, MLOps lifecycle and security standards.
3. Technical Execution
- Collaborate with ML engineers to productionalize models using Databricks, MLflow, Azure ML, or equivalent CI/CD MLOps frameworks.
- Guide teams on feature engineering, model selection, hyperparameter tuning, and validation for statistical and machine learning models.
- Encourage adoption of reusable data assets, API-based integrations, and modular code frameworks.
- Oversee econometric modeling, causal inference studies, and time-series forecasting for business-critical decision-making.
- Champion model lifecycle management, including version control, retraining pipelines, and performance drift monitoring.
4. Business Intelligence & Data Storytelling
- Supervise the creation of advanced BI dashboards and insight layers powered by predictive and generative AI.
- Translate complex statistical outputs into actionable business narratives for executive decision-making.
- Champion KPI alignment and measurement frameworks, ensuring analytics deliver quantifiable value to revenue, growth, retention, and operational efficiency metrics.
5. Agile Program Management
- Manage sprint planning, backlog prioritization, and resource allocation across concurrent projects.
- Track velocity, quality metrics, and ROI impact for each product stream.
- Coach teams on agile best practices and outcome-oriented delivery.
Qualifications
Required
- 10+ years of total experience with at least 3 years in a tech lead capacity.
- Proven expertise in Python, SQL, statistical modeling (e.g., regression, time-series, causal inference) and one or more of Power BI, Tableau, MicroStrategy.
- Strong foundation in data engineering, cloud architecture (Azure/AWS/GCP), and ML model deployment.
- Experience leading cross-functional agile teams with engineers, analysts, and data scientists.
- Excellent communication and stakeholder management skills — capable of simplifying complex data stories for business leaders.
Preferred
- Experience in forecasting models, econometrics, and experimental design (A/B testing, uplift modeling).
- Exposure to MLOps tools (MLflow, Kubeflow, Airflow, Azure ML pipelines) and monitoring frameworks for models in production.
- Familiarity with agentic AI, LLM-based product development, or generative analytics use cases.
- Prior experience building analytics or AI solutions in B2B, SaaS, or digital transformation contexts.
- Certifications in Agile, Cloud (Azure ML, AWS Data Analytics), or Data Science specialization are a plus.
Key Traits
- Hands-on technologist who can code, review, and guide with empathy.
- Strategic thinker who connects product vision with execution.
- Comfortable operating in ambiguity and scaling solutions from POC to enterprise rollout.
- Passionate about mentoring teams and embedding a data-first, growth-oriented mindset.

About Ampera Technologies
About
At Ampera Technologies, we empower businesses with cutting-edge data analytics, quality assurance, and data engineering solutions
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About the company
We are an AI diffusion company. We partner with midmarket companies in asset-heavy, regulated industries to co-build deeply industry-specific agentic and machine learning solutions, which then get diffused across the industry through revenue-share and equity-linked models.
Our Past
We have built and sold two companies, one of which was an AI company. Our founders and leaders are Math PhDs, Ivy League University Alumni, Ex-Googlers, and successful entrepreneurs.
Team
Our team of 20+ employees consists of data scientists, AI/ML Engineers, and mathematicians from top engineering and research institutes such as IITs, CERN, IISc, UZH. Our team includes academicians, IBM Research Fellows, and former founders. This role focuses on healthcare and RCM, working alongside our AI/ML engineers, data scientists and domain specialists.
Key Responsibilities
- Lead product ideation, solution design, and technical strategy from concept to execution.
- Drive end-to-end product development, translating business needs into scalable technical solutions.
- Build and lead engineering teams to deliver high-impact products.
- Design and develop robust data systems to process and structure unorganized data from ERP/CRM platforms.
- Leverage AI and domain expertise in healthcare/RCM to build innovative solutions.
- Drive technology-led growth, with a focus on product scalability and business outcomes.
\Required Skills & Experience
- 15–20 years of experience in technology leadership, preferably as a CTO or senior technology leader.
- Proven experience building and/ or exiting startups.
- Strong expertise in data engineering, complex data systems, and unstructured data processing.
- Experience with AI-driven products, preferably in healthcare or Revenue Cycle Management (RCM).
- Strong product thinking, system design, architecture, and end-to-end execution capabilities.
- Ability to translate business requirements into technical roadmaps and scalable products.
About the role
You will be a pivotal member of the leadership team, responsible for driving the company's product and platform strategy while overseeing engineering excellence across AI, data, platform, DevOps and infrastructure. This is a mission-critical role for an engineering leader who is both strategic and hands-on, and who can build scalable technologies for global enterprise clients in a fast-paced innovation ecosystem.
Reports to: CEO · Location: Bengaluru, India — hybrid, 3 days a week in office
What you will do
Technology & product leadership
- Define and drive the technology vision, architecture and long-term platform roadmap.
- Oversee the architecture, design and delivery of highly scalable enterprise systems.
- Ensure engineering excellence, velocity and reliability across the product lifecycle.
Engineering & platform management
- Lead platform engineering, product technology, DevOps, infrastructure and Quality Engineering.
- Build robust cloud-native systems using the Azure, AWS and GCP ecosystems.
- Oversee operational effectiveness, including uptime, production reliability and cost optimisation.
Innovation & AI strategy
- Spearhead Mission AI by developing scalable, production-grade AI/ML and GenAI capabilities.
- Own the GenAI/LLM solutions architecture.
- Core specialisation in AI agents and autonomous workflows, data extraction and intelligent automation.
- Direct hands-on architectural oversight of large language models, applied AI and multi-layered deep learning products.
- Extensive expertise in building intelligent document automation systems — similar in complexity to patent parsing, legal workflow automation and structured decision intelligence tools.
Technical leadership
- A proven track record overseeing product architecture, tech strategy and cross-functional engineering execution across core full-stack and AI platforms.
- Collaborate with executive leadership on business strategy, client requirements and product delivery.
- Build, mentor and scale high-performing engineering teams with a growth mindset.
- Establish a strong technology culture grounded in ownership, innovation and continuous learning.
What success looks like
- Mission AI: build a world-class AI system leveraging GenAI, ML and enterprise-grade data engineering.
- Hyper-scaling: architect and scale the platform to match global industry leaders in the IP space.
- Culture building: develop a strong engineering organisation with high ownership, performance and innovation DNA.
Qualifications & experience
- Preferably under 15 years of enterprise software engineering experience across B2B SaaS or technology-first companies; fewer is fine for an exceptional engineer.
- A proven track record of taking early-stage AI/ML prototypes and scaling them into robust enterprise SaaS platforms featuring multi-agent orchestration, complex workflows and decision intelligence.
- Experienced in building and mentoring agile, lean startup teams of full-stack and machine learning engineers from the ground up.
- Proven leadership in defining and executing technology strategy and platform roadmaps.
- Extensive cloud-native engineering experience with Azure, AWS and GCP.
Technical expertise
- Strong full-stack engineering background (Java, Python, JavaScript frameworks).
- Expertise with JS frameworks such as React, Angular and Node.js.
- Experience building and scaling distributed systems and microservices.
- Strong knowledge of databases (SQL, NoSQL), data modelling and unstructured data management.
- Strong understanding of Agile methodologies and tools (Atlassian, Git, CI/CD pipelines).
Behavioural & leadership competencies
- Product and delivery management expertise, end to end, including delivery and customer support.
- Excellent communication, with the ability to influence executive stakeholders.
- High technical proficiency combined with strong business acumen.
- Strong analytical and decision-making skills.
About the Company
As the world moves toward AI-native applications, one element matters more than anything: data.
We are building a platform that helps organizations unlock the value hidden within customer feedback. By centralizing data from multiple sources—including CRM platforms, support systems, collaboration tools, surveys, community forums, and customer conversations—into a unified intelligence layer, we enable teams to understand customer needs and make better product decisions.
Built on top of this foundation is an AI-powered platform that allows teams to query, monitor, and act on customer intelligence directly within their workflows. Our customers include some of the fastest-growing product-led technology companies as well as large global enterprises.
Backed by leading global venture capital firms, our engineering culture is AI-native from the ground up. Agents, LLMs, and applied machine learning are not side projects—they are central to how we build products. We operate at the cutting edge of agentic systems and continuously push the boundaries of what modern AI applications can achieve.
What You Will Do
- Convert product direction into phased technical plans, including estimates, milestones, dependencies, and risk assessments.
- Make thoughtful trade-offs across correctness, latency, user experience, AI/model behavior, reliability, cost, and delivery speed.
- Define clear ownership boundaries across frontend applications, BFF layers, backend services, agent workflows, ML platforms, and data contracts.
- Review ERDs, PRDs, design documents, and implementation plans to identify gaps before they become execution challenges.
- Drive planning and execution for complex initiatives while empowering area leads and senior engineers to maintain ownership.
- Partner closely with Product, Design, Engineering, and GTM teams to turn ambiguous problem statements into executable solutions.
- Influence technical direction through strong engineering judgment, architectural leadership, and hands-on involvement.
- Mentor senior engineers and contribute to engineering excellence through reviews, incident analysis, and proactive risk management.
What It Takes
- 9+ years of experience as a Senior Engineer, Technical Lead, or equivalent role.
- Demonstrated experience owning architecture and execution for large-scale product or platform initiatives spanning multiple teams.
- Strong foundation in distributed systems and modern software architecture.
- Exposure to agentic AI systems, machine learning engineering, MLOps platforms, and frontend/BFF architectures.
- Ability to own end-to-end product and technical problems rather than specializing exclusively in a single layer of the stack.
- Proven track record of converting ambiguity into actionable engineering plans.
- Excellent written communication skills, including design documentation, architectural reviews, trade-off analyses, and RCA documentation.
- Ability to challenge requirements constructively and collaborate effectively across Product, Design, Engineering, and GTM functions.
- High ownership mindset, attention to detail, and a low-ego, collaborative approach.
About the company
We are an AI diffusion company. We partner with midmarket companies in asset-heavy, regulated industries to co-build deeply industry-specific agentic and machine learning solutions, which then get diffused across the industry through revenue-share and equity-linked models.
Our Past
We have built and sold two companies, one of which was an AI company. Our founders and leaders are Math PhDs, Ivy League University Alumni, Ex-Googlers, and successful entrepreneurs.
Team
Our team of 20+ employees consists of data scientists, AI/ML Engineers, and mathematicians from top engineering and research institutes such as IITs, CERN, IISc, UZH. Our team includes academicians, IBM Research Fellows, and former founders. This role focuses on healthcare and RCM, working alongside our AI/ML engineers, data scientists and domain specialists.
Work you’ll do
We are looking for an experienced Project Manager cum Lead to own product decisions and project delivery for our healthcare AI pod. You will lead engineers building AI agents, automations and data workflows for healthcare revenue cycle management, while remaining hands-on in solution design, code reviews, prototyping and technical problem-solving.
You will work directly with client CXOs, billing leaders and operations teams to identify problems, agree measurable outcomes and decide what to build first.
You will translate those decisions into a practical roadmap, manage delivery and remain accountable for adoption and performance in production.
The work includes payer-portal automation, claim status and document retrieval, voice-based payer follow-up, analysis of revenue-cycle bottlenecks and AI-assisted practice insights.
Responsibilities
- Lead the healthcare AI pod, setting technical direction, reviewing engineering work, mentoring engineers and resolving delivery blockers.
- Work with client CXOs and operational leaders to define business problems, establish baselines and agree measurable outcomes.
- Own product discovery and prioritization, translating user needs into a roadmap, requirements and clear acceptance criteria.
- Make solution and build-versus-buy decisions, choosing between APIs, rules-based automation, RPA and AI based on reliability, cost and business value.
- Stay hands-on through architecture and code reviews, targeted prototypes and troubleshooting of complex production issues.
- Own project scope, estimates, milestones, resources and dependencies. Manage changes and explain their impact on cost, timelines and outcomes.
- Lead executive reviews, communicate progress and risks clearly, and secure decisions needed to keep delivery moving.
- Establish evaluation, security and release criteria, including monitoring, exception handling and human escalation.
- Work with billing and operations teams through rollout, adoption and ongoing improvement, measuring results against agreed baselines.
- Identify capabilities that can be reused across engagements and incorporate them into the product roadmap.
Who you are
You are an engineering leader who remains close to the code and takes responsibility for what the team delivers. You can investigate a technical issue with an engineer, make a product prioritization decision with an operations leader and explain the trade-offs to a client executive. You bring structure to unclear problems, make decisions with incomplete information and know when to challenge a request or change direction. You balance delivery speed with reliability, security and maintainability, and support your decisions with evidence. You have led teams through production delivery, handled difficult stakeholder conversations and stayed accountable for adoption and business outcomes after launch.
Skills & Requirements
Must have
- At least 7 years of relevant engineering and technical leadership experience, with recent hands-on involvement in solution design, code reviews, prototyping and production troubleshooting.
- Experience leading engineering teams delivering AI or automation systems into live operations, with accountability for technical quality, delivery and business outcomes.
- Experience deploying and supporting LLM-based applications or AI agents, including retrieval, tool calling, evaluation, error handling and human escalation.
- Strong Python and SQL skills, with the ability to review code, assess API and data integrations, and guide browser or workflow automation using tools such as Playwright, Selenium or UiPath.
- Experience delivering applications on at least one cloud platform—AWS, Azure or GCP—with an understanding of containers, deployment pipelines, monitoring and operating costs.
- Experience making product decisions, including discovering user needs, prioritizing workflows, defining acceptance criteria and balancing client-specific requirements against reusable capabilities.
- Experience managing client engagements from discovery through deployment and adoption, including scope, estimates, resource planning, dependencies and recovery of projects that have gone off track.
- Experience working directly with CXOs and senior operational leaders to agree outcomes, explain trade-offs, resolve conflicting priorities and manage expectations.
- Experience delivering healthcare or RCM solutions, with practical understanding of billing workflows, data quality issues and operational exceptions.
- Experience handling sensitive healthcare data and incorporating access controls, secure logging and approved data-handling practices into delivery.
- Ability to demonstrate your own technical contribution, a significant product decision and measurable outcomes from an engagement you led.
Preferred experience
- Experience delivering solutions for US healthcare providers or RCM companies, including working with US billing teams and payer workflows.
- Experience with practice-management or EHR integrations, payer portals, EOB/ERA data or analysis of revenue-cycle performance.
- Experience turning capabilities developed for individual clients into reusable products.
- Experience hiring and developing engineering teams.
- Experience managing delivery budgets, engagement profitability or a practice P&L.
Working with us
We are a young company, but we believe strongly in thinking long-term, while acting with urgency. Our ethos is rooted in innovation, efficiency and high-quality outcomes. We believe the future of work is AI-augmented and boundaryless.
Here are some of our guiding principles:
- Think in decades. Act in hours. As an independent company, our moat is time. While our decisions are for the long-term horizon, our execution will be fast – measured in hours and days, not weeks and months.
- Own the canvas. Throw yourself in to build, fix or improve – anything that isn’t done right, irrespective of who did it. Be selfish about improving across the organization – because once the rot sets in, we waste years in surgery and recovery.
- Use data or don’t use data. Use data where you ought to but not as a ‘cover-my-back’ political tool. Be capable of making decisions with partial or limited data. Get better at intuition and pattern-matching. Whichever way you go, be mostly right about it.
- Avoid work about work. Process creeps on purpose, unless we constantly question it. We are deliberate about committing to rituals that take time away from the actual work. We truly believe that a meeting that could be an email, should be an email and you don’t need a person with the highest title to say that out loud.
- High revenue per person. We work backwards from this metric. Our default is to automate instead of hiring. We multi-skill our people to own more outcomes than hiring someone who has less to do. We don’t like squatting and hoarding that comes in the form of hiring for growth. High revenue per person comes from high quality work from everyone. We demand it.
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.
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
Job Description – Squad Lead
Location: Kochi, Kerala
Experience: 10+ Years
Role: Squad Lead
Notice Period: Immediate to 30 Days
About the Role
We are looking for an experienced and technically strong Squad Lead to join our engineering team in Kochi. The ideal candidate will have 10+ years of software development experience, with strong expertise in Java, Spring Boot, Microservices, Angular, and AI technologies.
The Squad Lead will be responsible for leading a cross-functional engineering squad, driving technical excellence, mentoring team members, and ensuring the successful delivery of scalable and high-quality software solutions.
Key Responsibilities
- Lead and manage a software engineering squad, ensuring successful delivery of projects and product initiatives.
- Provide strong technical leadership and hands-on guidance to the development team.
- Design and develop scalable, secure, and high-performance applications using Java, Spring Boot, and Microservices.
- Drive the adoption and integration of AI/GenAI technologies into products and engineering solutions.
- Collaborate with frontend teams and contribute to applications developed using Angular.
- Define technical approaches, architecture, coding standards, and best practices.
- Conduct code reviews and ensure adherence to engineering and quality standards.
- Mentor and coach developers, helping them grow technically and professionally.
- Work closely with Product Managers, Business Analysts, Architects, QA, DevOps, and other stakeholders.
- Break down complex requirements into actionable technical tasks and sprint deliverables.
- Participate in solution design, estimation, planning, and technical discussions.
- Identify technical risks and proactively drive their resolution.
- Ensure timely delivery while maintaining high standards of code quality, performance, security, and maintainability.
- Promote Agile/Scrum practices and foster a culture of collaboration, ownership, and continuous improvement.
Required Skills & Experience
- 10+ years of experience in software development, with significant experience in technical leadership.
- Strong hands-on experience with Java and Spring Boot.
- Strong understanding and practical experience with Microservices architecture.
- Experience developing and integrating RESTful APIs.
- Good experience with Angular and modern frontend development practices.
- Exposure to AI/ML, Generative AI, or AI-powered application development.
- Proven experience in leading software engineering squads/teams.
- Strong understanding of software architecture, design patterns, scalability, and performance.
- Experience working in Agile/Scrum development environments.
- Strong problem-solving, analytical, communication, and stakeholder-management skills.
Good to Have
- Experience with AWS and cloud-native application development.
- Knowledge of AWS services such as EC2, S3, Lambda, ECS/EKS, RDS, API Gateway, and CloudWatch.
- Experience with CI/CD, Docker, Kubernetes, and DevOps practices.
- Exposure to event-driven architectures and messaging platforms such as Kafka.
- Experience with cloud security, observability, and application performance monitoring.
Leadership Competencies
The successful candidate should demonstrate:
- Proven experience leading and mentoring engineering teams.
- Strong ownership and accountability for delivery.
- Ability to make sound technical decisions and influence stakeholders.
- Excellent communication and collaboration skills.
- Ability to manage priorities and deliver under tight timelines.
- A continuous-learning mindset with an interest in emerging technologies, particularly AI and cloud.
Education
- Bachelor's or Master's degree in Computer Science, Engineering, Information Technology, or a related discipline.
Senior Product Manager – AI / B2B SaaS
Location: Bengaluru
Work Mode: Work from Office
Experience: 5+ years
Department: Product Management
About LeadSquared
LeadSquared is a leading Sales CRM for high-velocity revenue teams, helping businesses manage leads, sales processes, customer interactions, marketing, and revenue workflows at scale.
We serve businesses where large sales teams manage high volumes of leads and customer interactions, making speed, prioritisation, automation, and effective sales execution critical to revenue growth.
Role Overview
We are looking for a Senior Product Manager – AI to own the roadmap and end-to-end execution of AI products within LeadSquared.
Key Responsibilities
- Own the roadmap, prioritisation, and end-to-end execution for your AI product area.
- Understand customer problems and identify where AI can create meaningful, scalable value and translate them into clear product requirements and scalable solutions.
- Drive products from discovery and 0→1 development through launch, adoption, and iteration.
- Build and scale end-user-facing AI experiences that work reliably within enterprise workflows.
- Make informed product decisions considering quality, latency, and scale trade-offs in production AI systems.
- Work closely with Engineering, Design, AI/ML, Data, and GTM teams to ship high-quality products.
- Define and track product adoption, engagement, customer outcomes, and business impact.
- Drive GTM, adoption, and continuous product optimisation.
What We're Looking For
- 5+ years of Product Management experience.
- 2+ years of hands-on Product Management experience building AI products.
- Strong B2B SaaS product experience.
- Experience in 0→1 product development and launches.
- Strong product discovery, prioritisation, roadmap management, and execution skills.
- Familiarity with AI evaluations (evals), observability, guardrails, and human oversight.
- Data-driven approach with strong understanding of product metrics.
- Excellent communication, problem-solving, and stakeholder management skills.
- Candidates from Tier 1 / Tier 1.5 / Tier 2 colleges preferred.
Good to Have
- Experience building products using GenAI, LLMs, RAG, AI Agents / Agentic AI, or ML-based decision systems.
- Experience in CRM, SalesTech, MarTech, or Enterprise SaaS.
- Experience building AI products for sales, revenue, operations, or other enterprise users.
- Experience taking an AI capability from an early prototype to a reliable, scalable enterprise product.
- Candidates who have built AI side projects will have a preference. Share links to live products, prototypes, demos, GitHub repositories, agents, or apps you’ve built.
About Orenda
Orenda is a fintech-enabled financial services company founded in 2017 and based in Ahmedabad, Gujarat. We work as a corporate DSA and channel partner for leading banks and NBFCs, helping individuals, professionals, and MSMEs access suitable financial solutions across business loans, personal loans, home loans, loan against property, and professional loans.
At Orenda, we combine financial expertise, technology, and streamlined processes to simplify the lending journey. We are building our own lending-tech platform to improve operational efficiency, strengthen lender and partner integrations, and develop technology-driven solutions that support our evolving business needs.
About the role
We're looking for a Lead Software Engineer who enjoys building as much as designing. You'll shape how our systems are architected, write a good share of the code yourself, and lead a team of 3 to 5 engineers, including AI/ML engineers.
This is a hands-on leadership role, not a pure management or architecture position. Your time will be roughly split like this:
Share of time
Leading the team ~30%
Solution design ~30%
Hands-on coding ~30%
Deployment and infrastructure~10%
What you'll work on
Solution design and architecture
• Turning business needs into technical designs that are practical to build and easy to maintain
• Making architecture decisions across services, integrations and data flows
• Estimating, scoping and planning new features with business and product stakeholders
• Shaping the solution design for AI/ML use cases alongside the AI/ML engineers
Engineering and delivery
• Writing production code in Python and Node.js
• Rolling out new features across our internal and partner-facing platforms, including our CRM and partner portal
• Continuously improving existing systems for performance, reliability and code quality
• Reviewing code and setting engineering standards for the team
Infrastructure and cloud
• Maintaining and upgrading our infrastructure, including a planned move to a major cloud platform
• Owning deployments and production stability together with the team
• Working with event-driven and messaging systems (NATS today, Kafka planned)
Team leadership
• Leading and mentoring a team of 3 to 5 engineers
• Planning and prioritising work, unblocking the team, and making sure things ship
• Building a culture of ownership, clear documentation and quality
What we're looking for
• 5 to 8 years of software engineering experience, with hands-on coding in your recent roles
• Strong command of Python and Node.js
• Proven experience designing and building backend systems and microservices that run in production
• Hands-on experience deploying and running workloads on at least one major cloud platform (AWS, Azure or GCP)
• Solid working knowledge of PostgreSQL
• Experience with messaging or event streaming systems such as NATS, Kafka or RabbitMQ
• Experience leading or mentoring a small engineering team
• Comfort estimating effort, breaking down features and planning delivery
• Enough understanding of AI/ML systems to guide their solution design and integration
• Clear communication with both technical and non-technical stakeholders
Good to have
• Experience working at a fintech, lending or financial services company
• Hands-on experience with Kafka
• Experience leading an infrastructure upgrade or cloud migration
• Experience building or scaling CRM or partner-facing portal products
Why Join Us?
- Build a growing lending-tech platform: Play a key role in shaping the technology behind a growing financial services business.
- Own technical decisions: Contribute directly to architecture, engineering standards, and technology direction.
- Stay hands-on: Combine solution design and technical leadership with meaningful coding responsibilities.
- Work with emerging technologies: Collaborate with AI/ML engineers and contribute to evolving platform capabilities.
- Lead and grow a team: Mentor engineers and help build a strong engineering culture as the technology function scales.
- Make a measurable impact: Build systems that improve operational efficiency and support business growth.










