About the Company: An early-stage, high-growth AI security startup.

Position Overview:

We are seeking a motivated Junior Backend Engineer to join our client's growing engineering team. In this role, you will work alongside senior engineers to build, test, and maintain backend services that underpin our client's AI security products. This is an excellent opportunity for an early-career engineer to grow quickly, work on real-world AI security problems, and be mentored by a team with deep experience in both software engineering and cybersecurity.

Reporting To: Senior Backend Engineer/ Head of Engineering

Key Responsibilities:

• Develop and maintain backend services and APIs under the guidance of senior engineers, ensuring code quality, test coverage, and documentation.
• Write clean, well-tested Java and Python code for microservices, batch jobs, and data processing pipelines on the platform.
• Assist in integrating AI/ML model output (security alerts, threat signals) into backend data flows and dashboards.
• Build and maintain database schemas, optimise queries, and ensure data integrity across PostgreSQL and NoSQL datastores.
• Participate in code reviews, learning from feedback, and progressively taking ownership of feature-level development.
• Write unit tests, integration tests, and assist the QA team with functional testing of backend services.
• Support deployment activities via CI/CD pipelines and assist in monitoring and troubleshooting production issues.
• Maintain clear technical documentation for APIs, services, and workflows.
• Engage proactively with the team's learning culture — staying updated on backend engineering best practices and AI security fundamentals.

Education:

• B.E./ B.Tech in Computer Science, Information Technology, Electronics & Communication, or a related discipline.

Experience:

• 2–3 years of backend development experience in a professional or internship setting.
• Hands-on contribution to at least one production or near-production backend system is required.

Technical Skills – Core:

• Proficiency in Java (core Java concepts, OOP, Spring Boot basics) and Python (scripting, REST APIs with Flask or FastAPI).
• Understanding of RESTful API design principles and experience consuming or building APIs.
• Familiarity with SQL databases (MySQL/ PostgreSQL): writing queries, understanding indexes, and basic schema design.
• Basic knowledge of version control with Git: branching, merging, pull requests.
• Exposure to containerisation with Docker; familiarity with cloud environments (AWS, GCP, or Azure) is a plus.
• Understanding of software development lifecycle, Agile/Scrum methodologies, and unit testing frameworks (JUnit, pytest).

AI & Security Awareness:

• Basic awareness of cybersecurity concepts: secure coding practices, common vulnerabilities (OWASP), and the importance of data protection.
• Curiosity about AI and machine learning; a basic understanding of how ML models are trained and deployed is desirable.
• Willingness to learn AI security-specific topics (adversarial ML, model security, LLM safety) on the job with structured mentorship.

Soft Skills:

• Strong desire to learn and grow in a fast-paced startup environment.
• Good communication skills and the ability to ask the right questions when requirements are unclear.
• Team player with a collaborative, positive attitude.
• Attention to detail and commitment to writing clean, maintainable code.

Nice-to-Have/ Preferred:

• Final-year academic project or internship experience in a security, AI/ML, or data engineering domain.
• Exposure to NoSQL databases (MongoDB, Redis) or message queues (Kafka, RabbitMQ).
• Participation in hackathons, open-source projects, or competitive programming platforms (LeetCode, HackerRank).
• Familiarity with any ML framework (TensorFlow, PyTorch, scikit-learn), even at a conceptual level.

About the Company: An early-stage, high-growth AI security startup.

Position Overview:

We are looking for a Senior Backend Engineer to join our client's core platform team and help architect, build, and scale the backend systems that power AI security products. You will work closely with AI/ ML researchers, security engineers, and product leads to translate cutting-edge AI security requirements into robust, production-grade services. This role offers the opportunity to contribute to systems that protect AI models deployed by some of the most critical organisations in the world.

Reporting To: Head of Engineering

Key Responsibilities:

• Design, develop, and maintain highly scalable, reliable, and secure backend services and microservices that form the core of the company's AI security platform.
• Build and expose RESTful and gRPC APIs consumed by internal services, ML inference pipelines, and external enterprise customers.
• Architect event-driven data pipelines to ingest, process, and serve real-time telemetry from AI model monitoring agents deployed at client sites.
• Implement authentication, authorisation (OAuth 2.0, RBAC), and end-to-end encryption mechanisms across all platform services.
• Collaborate with AI/ML engineers to integrate model-scanning, adversarial detection, and threat-intelligence modules into production backend workflows.
• Lead technical design reviews, define system architecture decisions, and document engineering standards for the team.
• Conduct code reviews, enforce code quality, and mentor junior engineers on best practices in backend development and security engineering.
• Own the reliability and performance of production services: establish SLIs/SLOs, write runbooks, and lead incident response.
• Engage with DevOps/Platform Engineering to ensure CI/CD pipelines, containerisation (Docker/Kubernetes), and cloud deployments follow security-by-design principles.
• Stay current on emerging AI security threats (OWASP LLM Top 10, MITRE ATLAS) and incorporate defence patterns into platform design.

Education:

• B.E./ B.Tech in Computer Science, Information Technology, or a related engineering discipline.
• M.Tech or equivalent postgraduate degree is an advantage, but not mandatory.

Experience:

• 4–5 years of hands-on backend software development in production environments.
• Proven track record of owning services end-to-end: design, build, deploy, monitor, and iterate.
• Experience working in a security-focused, platform, or AI/ ML-adjacent product company is highly preferred.

Technical Skills – Core:

• Strong proficiency in Java (Spring Boot/ Quarkus) and Python (FastAPI/ Django/ Flask) — both languages in active use.
• Deep understanding of RESTful API design, gRPC, and asynchronous messaging patterns (Kafka, RabbitMQ).
• Solid experience with relational databases (PostgreSQL, MySQL) and NoSQL stores (MongoDB, Redis, Elasticsearch).
• Proficiency with containerisation (Docker) and orchestration (Kubernetes/ EKS/ GKE).
• Hands-on experience with cloud platforms: AWS, GCP, or Azure — including IAM, VPC, KMS, and secure storage.
• CI/ CD tooling: GitHub Actions, Jenkins, GitLab CI, or equivalent.

Security & AI Domain Knowledge:

• Working knowledge of application security fundamentals: OWASP Top 10, threat modelling, secure coding standards.
• Basic familiarity with AI/ML security concepts — adversarial attacks, model inference risks, prompt injection, and data poisoning — sufficient to make informed design decisions.
• Understanding of compliance and governance frameworks relevant to AI systems (ISO 27001, SOC 2, DPDP Act 2023) is a plus.

Soft Skills:

• Strong written and verbal communication skills in English; ability to articulate technical trade-offs to nontechnical stakeholders.
• High ownership mindset; comfortable leading initiatives and driving outcomes independently.
• Effective collaborator across distributed, cross-functional teams.

Nice-to-Have/ Preferred:

• Exposure to adversarial ML tools: ART (Adversarial Robustness Toolbox), Foolbox, CleverHans, or equivalent.
• Experience building or integrating LLM security guardrails (prompt injection filters, output scanners).
• Familiarity with SIEM/SOAR integrations and security telemetry pipelines.
• Open-source contributions or publications in AI security, backend systems, or applied ML.
• Certifications: AWS Certified Solutions Architect, CKAD, CEH, or equivalent.

What's on Offer:

• Competitive compensation with performance-based bonuses.
• Equity/ ESOP participation in a high-potential AI security startup.
• Direct exposure to cutting-edge AI security research and enterprise-scale deployments.
• Collaborative, flat culture with strong engineering values.
• Hybrid work flexibility; modern office in Ahmedabad, Gujarat.
• Comprehensive health insurance (employee + family) and professional development budget.

About the Company: An incubator for startups.

Job Role:

The Venture Legal Analyst Program is a structured 24-month engagement designed to build transaction-ready legal professionals specializing in venture capital, start-up governance, regulatory compliance, and fund operations.

Compliance, Documentation and VC Basics:

1. Venture capital fundamentals, including term sheets, equity instruments, cap tables, liquidation preference and anti-dilution.
2. Companies Act compliance relating to board approvals, allotments, share transfers and filings.
3. Program-related transactions such as grant agreements, service agreements, MOUs and share transfers.
4. Drafting and reviewing commercial agreements, including employment, consultancy, vendor agreements and NDAs.

Full-Scale VC Transaction Exposure:

1. Due diligence coordination and data room management.
2. Drafting and reviewing SSA, SHA and disclosure documents.
3. Managing transaction trackers and coordinating with external law firms.
4. Participating in negotiation calls and observing risk allocation strategies.

Independent Transaction Leadership and Regulatory Exposure:

1. Leading smaller transactions end-to-end.
2. Drafting and negotiating core documentation.
3. Managing closing mechanics and compliance filings.
4. Exposure to exit transactions and regulatory compliance, including SEBI and AIF frameworks.

Portfolio Governance and Start-up Advisory:

1. Board documentation and shareholder governance.
2. Founder disputes, ESOP structuring and governance restructuring.
3. Start-up advisory on entity structuring, employment and compliance matters.
4. Strategic legal risk assessment and preventive compliance.

Must have skills:

1. Strong drafting and analytical skills.
2. Ability to work in dynamic, high-responsibility environments.

Good to have skills:

1. Interest in venture capital and startup ecosystems.
2. Ability to work in dynamic, high-responsibility environments.

Qualifications:

1. Law Graduates 3-year or 5-year course.
2. Prior internship or working experience in the General Corporate, PE/VC vertical.

About the Organization: An incubator for startups.

Job role:

This will be a mix of research, operations and startup interfacing roles. The candidate must ideally possess excellent business analysis, analytical and communication skills. The Analyst program is a full-time role and will be for a duration of 24 months. The program is designed to provide candidates with the opportunity to build skills in business model design, investments, and other startup-relevant skills.

Program-related activities:

1. Work with the team for all program-related execution.
2. Build sector knowledge and contribute towards creating content, including Sector landscaping, use-cases and other thought leadership.
3. Work actively to help prepare IM's, one-pagers and other stakeholder reports.
4. Provide advisory and support services to program portfolio companies.
5. Facilitate investments and support start-ups in their fundraising.
6. Interact and maintain relationships with portfolio companies, mentors and other stakeholders.
7. Create timely portfolio update reports and continuously monitor the performance of portfolio companies.
8. Deal scouting and analysis for new investment and incubation opportunities.

Must have skills:

1. Analytical and problem-solving skills.
2. Passion to support the start-up ecosystem.

Good to have skills:

1. Knowledge and understanding of technologies such as robotics, AI, and IoT across various sectors.
2. Ability to use tools such as Notion, Tracxn, CB Insights, basic CRMs, etc.
3. Excellent spreadsheet skills.

Qualifications:

1. Graduate/Post Graduate degree.
2. 0-2 years’ experience, preferably in a start-up ecosystem.