Engineering Manager

About the Role

We are looking for a Full Stack AI Engineer who can take an ambiguous problem and turn it into a complete, production-ready AI product.

This is a builder role.

You will work across the entire stack — AI models, agents, backend services, APIs, databases, data pipelines, frontend applications, infrastructure, and production deployment. You should be comfortable deciding what needs to be built, writing the code, deploying it, measuring whether it works, and continuously improving it.

We are not looking for someone who only builds notebooks, trains models, writes prompts, or creates architecture diagrams for another team to implement. We want engineers who ship complete products.

A typical project might involve designing an agentic workflow, building a retrieval pipeline, writing Python APIs, creating a React interface, integrating enterprise data, deploying to Kubernetes, implementing evaluations, and debugging the application in production.

The distance between an idea and working software should be measured in weeks, not quarters.

This role is based in Hyderabad and is 6 days per week in the office.

We are looking for:

1. A person that can smoothly navigate extreme ambiguity
2. Full stack software builder
3. AI depth, must have built a production AI system
4. Excellent top-notch communication and stakeholder management
5. Prioritizes growth over work-life balance

What You'll Do

Build AI Products End-to-End

• Own AI applications from problem definition through architecture, development, deployment, and production operation.
• Translate ambiguous product and business requirements into working software.
• Build across AI/ML, backend services, APIs, databases, frontend interfaces, data pipelines, authentication, infrastructure, and observability.
• Rapidly prototype, test with real users and data, and turn successful ideas into production-grade systems.
• Make pragmatic engineering decisions based on speed, reliability, simplicity, maintainability, and user value.

AI, LLMs & Agents

• Build production applications using commercial and open-source foundation models.
• Design RAG systems, agentic workflows, tool/function calling, structured outputs, memory, human-in-the-loop workflows, and multi-agent systems where appropriate.
• Work with frameworks such as LangGraph, LangChain, Semantic Kernel, LlamaIndex, or equivalent tools.
• Build retrieval systems using embeddings, vector search, BM25, hybrid retrieval, reranking, metadata filtering, and knowledge graphs.
• Design prompt and context engineering strategies for complex workflows.
• Evaluate model choices based on accuracy, latency, reliability, security, and cost.
• Build automated evaluations and regression tests for AI behavior.
• Fine-tune or adapt models when prompting and retrieval are insufficient.

Backend, Frontend & Data

• Build production backend systems primarily in Python using FastAPI, Flask, Django, or similar frameworks.
• Design APIs, asynchronous workflows, background jobs, queues, caching layers, and event-driven systems.
• Work with PostgreSQL, SQL Server, MongoDB, Redis, Snowflake, and other production data stores.
• Build modern applications using React, Next.js, TypeScript, JavaScript, or equivalent frameworks.
• Create interfaces for copilots, conversational AI, workflow automation, analytics, review queues, and operational applications.
• Implement streaming responses, real-time updates, authentication, permissions, and API integrations.
• Build ingestion and transformation pipelines for structured and unstructured enterprise data.
• Work with documents, databases, APIs, event streams, images, logs, and operational datasets.
• Maintain provenance, permissions, metadata, and traceability across enterprise information.

ML & Computer Vision

• Use classical ML or deep learning when it is better suited to the problem than an LLM.
• Build systems involving classification, forecasting, anomaly detection, ranking, recommendations, optimization, or prediction.
• Build computer-vision applications involving detection, classification, segmentation, OCR, tracking, or image/video analysis.
• Work with PyTorch, TensorFlow, Hugging Face, OpenCV, or equivalent tools.
• Understand model development, evaluation, inference, and productionization.

Deploy & Operate What You Build

• Deploy applications across AWS, Azure, GCP, on-premises, hybrid, or edge environments.
• Containerize and operate applications using Docker and Kubernetes.
• Build CI/CD pipelines, automated testing, monitoring, and observability.
• Own reliability, latency, availability, security, evaluation, cost, and scalability.
• Debug failures across application code, AI models, data, infrastructure, and integrations.
• Build retries, fallbacks, rollback mechanisms, and human intervention into critical systems.

Integrate With Enterprise Systems

• Connect AI applications to enterprise platforms, databases, APIs, and operational systems.
• Integrate with systems such as ERP, MES, PLM, CRM, data warehouses, IoT platforms, document repositories, and legacy applications.
• Work within enterprise networking, security, and data-governance constraints.
• Implement authentication, authorization, secrets management, auditability, permissions, and data isolation.
• Build AI systems capable of safely operating on sensitive enterprise data.

What You Bring

• 5+ years of software engineering experience, with meaningful experience building AI/ML-powered products. Exceptional candidates with less experience but strong demonstrated ability will be considered.
• Strong hands-on programming ability in Python.
• Experience building complete production applications rather than isolated models, notebooks, or proofs of concept.
• Strong backend fundamentals including APIs, databases, distributed systems, and application architecture.
• Experience with React, Next.js, TypeScript, JavaScript, or equivalent frontend technologies.
• Strong understanding of LLMs, RAG, agents, tool calling, embeddings, vector search, prompt/context engineering, AI evaluation, and ML fundamentals.
• Experience with SQL and production databases.
• Experience with at least one major cloud platform: AWS, Azure, or GCP.
• Experience with Docker, Kubernetes, or equivalent production infrastructure.
• Understanding of production AI concerns including reliability, latency, security, observability, evaluation, and cost.
• Strong debugging skills across the full stack.
• Ability to independently turn loosely defined requirements into working software.
• Strong product judgment, high agency, technical curiosity, and a bias toward shipping.
• Bachelor's degree in Computer Science, Engineering, Data Science, or a related field, or equivalent demonstrated experience.

Preferred / Top-Candidate Signals

• You've independently shipped an AI application from database → backend → AI → frontend → production.
• You've built production RAG or agentic systems, not just demos.
• You've used LangGraph, LangChain, Semantic Kernel, LlamaIndex, or similar frameworks.
• You understand when not to use an LLM or agent.
• You've worked with hybrid retrieval, reranking, vector search, or knowledge graphs.
• You've built with both commercial and open-source models.
• You've deployed ML or computer-vision systems into production.
• You have experience with React/Next.js + Python/FastAPI or a comparable modern stack.
• You have experience with Kubernetes, cloud infrastructure, and production observability.
• You have integrated software with complex enterprise or industrial systems.
• Experience in manufacturing, industrial, supply chain, logistics, engineering, energy, aerospace, automotive, or other physical-world environments is a strong plus.
• You've built meaningful side projects, open-source software, startups, or substantial systems outside your assigned responsibilities.
• You have a history of turning vague ideas into shipped products.

What Makes Someone Exceptional

The strongest engineers in this role combine three abilities:

AI Engineering — Choose the right model, retrieval approach, agent architecture, evaluation method, or ML technique.

Software Engineering — Build everything around the intelligence: frontend, backend, data, APIs, infrastructure, security, integrations, and deployment.

Product Judgment — Understand what actually needs to be built and rapidly turn it into something users can use.

A typical week might involve designing an agent workflow, writing FastAPI services, building a React interface, creating a retrieval pipeline, connecting enterprise data, deploying to Kubernetes, implementing evaluations, and debugging real-world behavior.

You should not need five different teams to turn an idea into a working product. You should be able to build.

Why This Role

• Build entire products, not isolated models or prototypes.
• Own the full stack: AI, backend, frontend, data, infrastructure, and deployment.
• Ship quickly: move from idea to working software in weeks.
• Work across modern AI: LLMs, agents, RAG, ML, computer vision, optimization, and enterprise data.
• Solve real-world problems: build software used in complex operational environments.
• See your work in production: own the path from first commit to real users.
• Compensation is flexible for exceptional candidates. 

Total Experience:6months to 1 Year

Notice: Immediate Joiners

• Good experience of 1-2 years in sourcing from different channels
• Solid knowledge of sourcing techniques (e.g. social media recruiting and LinkedIn) 
• Should have basic technical knowledge of technologies used in IT & eCommerce (Java, SAP, Springboot, Scrum, product management, Digital marketing etc) 
• Strong communication and influencing skills  
• Source, screen, and conduct initial technical interviews with qualified candidates for all the positions along with the business leaders, and schedule follow-up interviews.
• Interaction with the relevant candidates, briefing them about the requirement
• Evaluate the technical skills of candidates and organize next interview rounds with leaders. 
• Initiate search for lateral recruitment by executing a complete search of the database as per the requirements to find relevant candidates
• Build talent pipeline for today and tomorrow with passive sourcing ability 
• Execute a complete search of the database as per the requirements to find relevant candidates
• Maintaining and updating the database of the candidates
• Understanding of business teams & their requirements
• Strong data analysis skills, ability to perform data analysis and make data-driven decisions 
• You are a technology enthusiast, you care about how things work and you can successfully collaborate with technical experts & leaders
• Ability to understand the organizational fit for the needs of the company 
• Experience recruiting for IT, eCommerce, Data Engineering talent
• Experience working with recruiting tools and systems, including resume databases, internet sourcing tools, and spreadsheets 
• Familiarity with Applicant Tracking Systems and resume databases 

Digital Marketing Expert - B2B ABM & Performance

About ProductNova:

ProductNova is a fast-growing product development startup. We are a team of Product and Business Growth Experts enabling organizations in building new Product Portfolios, Transform into Product organizations, Identify business opportunities, Innovate and Scale Businesses.

For early-stage organizations and startups, we shape ideas into products, identify the right customer base and product market fit, define the product, provide marketing and sales enablement, plan the GTM, launch, iterate and scale.

For established organizations, we Transform them into product organizations, identify business & product areas to scale and help revamp the products across new regions and customer segments. We enable innovation, build new product portfolios and help grow the businesses Exponentially.

We are also building our own B2B SaaS Products

The Role:

As a Digital Marketing Expert at ProductNova, you will play a pivotal role in shaping and executing comprehensive digital marketing strategies to drive product and business growth. You will be responsible for driving marketing campaigns across channels and growing our businesses.

Key Responsibilities:

B2B SaaS Marketing Expertise: Lead generation, SEO, PPC, CRM tools, ABM, and data-driven campaigns. Excellence in aligning sales strategies, customer journey mapping, and delivering measurable growth through innovative marketing.

ABM And Performance Marketing: Identify, source and nurture high-value accounts, crafting personalized campaigns, optimizing paid channels, and measuring ROI across digital touchpoints. Align marketing with sales to accelerate pipeline and deliver scalable, impactful campaigns that balance brand visibility with revenue-focused outcomes.

Lead Generation: Build and optimize B2B and B2C Lead gen pipeline for ProductNova and its clients for their respective products and services across channels.

Digital Marketing Strategy: Formulate and execute robust digital marketing strategies aligned with ProductNova, our partner objectives and overall business goals. Tweak and optimize existing strategies to grow revenue 2X.

Campaign Management: Oversee the end-to-end management of digital marketing campaigns, ensuring seamless execution and optimization for maximum ROI. Utilize data-driven insights to continuously refine and enhance campaign performance.

Channel Expertise: Demonstrate expertise across various digital marketing channels, including but not limited to Meta, Google, SEO, SEM, social media, Email marketing, and Content marketing. Identify new and emerging channels to explore and incorporate into the overall marketing mix.

Analytics and Reporting: Implement robust analytics frameworks to measure and analyze the performance of digital marketing campaigns.

Qualifications:

• Any professional degree/MBA in Digital marketing.
• Min 2 yrs+ experience in B2B Digital marketing with a focus on product and business growth.
• Strong leadership skills with the ability to motivate a high-performing team.
• In-depth knowledge of digital marketing channels, tools, and analytics platforms.
• Exceptional analytical and problem-solving abilities.
• Excellent communication and interpersonal skills.

If you are a results-driven digital marketing professional with a passion for driving business growth, we invite you to join our dynamic team at ProductNova.

Job Requirements:

•        experience with API development, Rest API and Web socket

Proven experience in software and application development, preferably as a .NET Developer

• Experience in working with SQL Server, .net core, ASP.NET framework and architectural patterns such as MVC
• Good understanding in Web API/Rest API
• Good at HTML, CSS3, jQuery and Java Script/Typescript
• Ability to take quick decisions while working in a fast-paced environment
• Strong understanding of Agile methodologies.

Responsibilities and Duties:

• Develop software solutions by studying information needs; conferring with users, studying systems flow, data usage and work processes, investigating problem areas, following the software development lifecycle
• Ensure high-level performance and responsiveness of all the .NET applications.
• Solid understanding of the data structure & algorithms.
• Prepare and install solutions by determining and designing system specifications, standards and programming
• Provide information by collecting, analyzing and summarizing development and service issues
• Understand business needs and know how to create the tools to manage them
• Production quality code is must to have better performance of the application.
• Should think out of the box and research on to adapt optimized technical solutions.

website: www.glansolutions.com

Job Description:

Candidate must have 2 to 5-years of experience in various phase of development of a python-based application or API development.

Requirements:

Must Have:  Strong expertise in PYTHON and its built-in data structures, developing API using flask or fastapi, data wrangling using standard python frameworks like pandas, NumPy etc., integration of various applications (third party or inhouse) with python.

Good to Have: Deployment using Nginx, GUnicorn, IIS, docker and Kubernetes etc. Good understanding of optimization solutions like differential evolution. Hands on experience with python packages like Scipy.  Tkinter to make python-based applications.

Roles and Responsibilities:

• Understanding/gathering the requirements from stakeholder, formulating the problem, and leveraging AI/ML to solve the business problems.
• Integration of third party or in house application with python solution.
• Working on Deployment and optimization of various engineering problems using Numerical/Constraint optimization frameworks such as Differential Evolution and deploy a web-based API using Flask and Nginx/IIS.
• Unit testing of various python modules developed and testing of the API.

We are looking for a Frontend Developer who would be working on the bleeding edge of technologies. We work primarily with React, Typescript and Redux.

Responsibilities:

• Understand why a particular design was chosen and code accordingly.
• Will have to deliver clean bug-free unit-tested code with minimal guidance.
• Strive for continuous improvement by refactoring and applying best practices.
• Learn and adapt to new technologies as necessary.

Requirements:

• Must be proficient in React, Redux, Redux Toolkit and Typescript.
• Used Typescript for React Components.
• Unit Testing, Component Testing, and Custom React hook tests with React Testing Library.
• Integration Tests with Cypress.
• Data Fetching libraries like Axios, React Query, RTK Query etc.
• Should have maintained React Components with Storybook.
• Experience contributing to open-source software will be preferred.
• Used various CSS stylings methods like CSS Modules, LESS, SCSS, Tailwind, Styled Components, Emotion etc.
• Should understand Git.
• Ability to work in a fast-paced and dynamic work environment.
• Exceptional interpersonal skills and demonstrated leadership abilities.

This requirement is for Data Engineer in Gurugram for Data Analytics Project. 

 Building ETL/ELT pipelines of data from various sources using SQL/Python/Spark 

 Ensuring that data are modelled and processed according to architecture and requirements both 

functional and non-functional 

 Understanding and implementing required development guidelines, design standards and best 

practices Delivering right solution architecture, automation and technology choices 

 Working cross-functionally with enterprise architects, information security teams, and platform 

teams Suggesting and implementing architecture improvements 

 Experience with programming languages such as Python or Scala 

 Knowledge of Data Warehouse, Business Intelligence and ETL/ELT data processing issues 

 Ability to create and orchestrate ETL/ELT processes in different tools (ADF, Databricks 

Workflows) Experience working with Databricks platform: workspace, delta lake, workflows, jobs, 

Unity Catalog Understanding of SQL and relational databases 

 Practical knowledge of various relational and non-relational database engines in the cloud (Azure 

SQL Database, Azure Cosmos DB, Microsoft Fabric, Databricks) 

 Hands-on experience with data services offered by Azure cloud 

 Knowledge of Apache Spark (Databricks, Azure Synapse Spark Pools) 

 Experience in performing code review of ETL/ELT pipelines and SQL queries Analytical approach 

to problem solvin

1. Expertise in building AWS Data Engineering pipelines with AWS Glue -> Athena -> Quick sight
2. Experience in developing lambda functions with AWS Lambda
3. Expertise with Spark/PySpark – Candidate should be hands on with PySpark code and should be able to do transformations with Spark
4. Should be able to code in Python and Scala.
5. Snowflake experience will be a plus