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Artificial Intelligence • Blockchain • Fintech • Financial Services • Cryptocurrency • NFT • Web3
Architect and develop scalable security platform services using Golang or Java. Define technical roadmaps, manage projects, collaborate with cross-functional stakeholders, write and review well-tested code, debug complex backend systems, improve operational reliability, and mentor engineers. The role focuses on security, compliance, privacy, secrets and key management, identity access management, vulnerabilities, and onchain security capabilities.
Top Skills:
Cloud TechnologyGenerative AiGoJavaService-Oriented Architecture
Cloud • Information Technology • Productivity • Security • Software • App development • Automation
Lead backend software engineering initiatives from technical design through launch. Solve complex architecture and reliability challenges, deliver shared solutions for engineering teams, establish code review and documentation standards, manage high-risk fixes, influence company-wide initiatives, mentor engineers, and make customer-focused technical decisions across cloud and developer productivity environments.
Top Skills:
AWSAzureContinuous DeploymentContinuous IntegrationGCPGoJavaKotlinNode.jsPythonScala
Enterprise Web • Mobile • Professional Services • Software
Build and own full-stack product features from ambiguous problems through deployment. Partner with Product and Design, make UX decisions, integrate LLM and agent capabilities into trustworthy product experiences, talk with users, instrument releases, and iterate based on usage. The role requires strong product judgment, user empathy, independent execution, and comfort using AI coding tools while collaborating with AI engineers on model behavior.
Top Skills:
Claude CodeCursorGithub CopilotLlm AgentsLlm ApisPrompting
Design, build and maintain cloud-native data platforms, pipelines, backend services and APIs on GCP. Enable analytics, reporting and AI/ML solutions (including Generative AI/LLMs). Lead end-to-end delivery, implement ETL/ELT frameworks (DBT, Airflow), apply ML techniques, ensure CI/CD/devops practices, mentor engineers, and collaborate with stakeholders to drive production-ready, scalable data and AI products.
As a Software Engineer – Data & AI Platforms, you will work closely with business stakeholders, product teams, data engineers and software engineers to create scalable and reliable solutions. You will participate in the complete software development lifecycle, from understanding business requirements and designing technical solutions to implementing, testing, deploying and supporting production applications.
You will build and maintain modern data pipelines that ingest, transform and curate large volumes of enterprise data from multiple sources. These data assets will support dashboards, analytics products, reporting solutions and AI applications. The role also requires developing backend APIs and cloud-native services that enable seamless integration between data platforms and business applications.
In addition, you will contribute to machine learning, Generative AI and intelligent automation initiatives by leveraging modern AI tools and cloud services. This includes identifying opportunities to streamline processes, improve user experiences and accelerate delivery through AI-powered solutions.
- Design, develop and maintain scalable software applications, backend services and APIs to support enterprise analytics, business processes and digital transformation initiatives.
- Build and optimize cloud-native data platforms and data pipelines that enable reliable ingestion, transformation and delivery of enterprise data for reporting, analytics and operational applications.
- Develop and manage ETL/ELT frameworks, data models and analytical datasets to ensure high-quality, trusted and business-ready data assets.
- Leverage cloud technologies, primarily Google Cloud Platform (GCP), to build secure, scalable and cost-effective data, software and AI solutions.
- Apply advanced analytics, machine learning and Generative AI capabilities to solve business challenges, improve decision-making and drive intelligent automation.
- Collaborate with business stakeholders and product teams to translate business requirements into scalable technical solutions and production-ready features.
- Own end-to-end solution delivery including requirements analysis, solution design, development, testing, deployment, monitoring and production support.
- Implement engineering best practices including code reviews, version control, automated testing, CI/CD and technical documentation to ensure solution quality and maintainability.
- Lead technical initiatives and mentor team members by providing technical guidance, sharing best practices and fostering engineering excellence.
- Drive innovation through AI, automation and emerging technologies, continuously identifying opportunities to enhance productivity, user experience and business value.
- Monitor, troubleshoot and optimize applications, data pipelines and cloud platforms to ensure reliability, performance, security and operational excellence.
- Work effectively in Agile cross-functional teams to deliver high-impact data, software and AI products that support enterprise objectives and customer needs.
- Master’s degree in Computer Science, Data Science, Software Engineering, Artificial Intelligence, Information Technology or a related discipline.
- Experience designing and delivering enterprise-scale data, analytics and cloud-native software solutions.
- Strong hands-on experience with Google Cloud Platform (GCP) services including BigQuery, Cloud Run, Cloud SQL, Dataflow, Dataproc, Pub/Sub and Vertex AI.
- Experience developing scalable backend services and APIs using Python, FastAPI or similar frameworks.
- Experience building modern data platforms using ETL/ELT frameworks, DBT, Apache Airflow and data modelling best practices.
- Experience with enterprise data platforms and databases such as PostgreSQL, Snowflake, Databricks, Oracle, SQL Server and BigQuery.
- Knowledge of Machine Learning, Advanced Analytics, Generative AI, Large Language Models (LLMs) and AI-assisted development tools.
- Experience implementing intelligent automation, AI-powered workflows and cloud-based analytics solutions.
- Experience with software engineering best practices including Git/GitHub, CI/CD, automated testing, code reviews and DevOps methodologies.
- Proven ability to lead technical work streams, mentor engineers and drive Agile delivery across cross-functional teams
- Experience collaborating with business stakeholders and translating business requirements into scalable technical solutions.
- Domain knowledge in Automotive, Manufacturing, Supply Chain Logistics.
What you need to know about the Delhi Tech Scene
Delhi, India's capital city, is a place where tradition and progress co-exist. While Old Delhi is known for its rich history and bustling markets, New Delhi is defined by its modern architecture. It's clear the region places a strong emphasis on preserving its cultural heritage while embracing technological advancements, particularly in artificial intelligence, which plays a central role in shaping the city's tech landscape, fueled by investments in research and development.
