AI Engineer (Full Stack Development) at Maker Lab

Mumbai, maharashtra, India -

Full Time

Start Date

Immediate

Expiry Date

22 Jul, 26

Salary

0.0

Posted On

23 Apr, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, TypeScript, JavaScript, Google Cloud Platform, AWS, Azure, LLM API Integration, Prompt Engineering, REST APIs, GraphQL, Cloud Functions, Firestore, Full-stack Development, System Architecture, Unit Testing, Workflow Automation

Industry

Marketing Services

Description

Grounded in a talent-centric mindset, Maker Lab is a marketing agency designed to build decentralised technology-led agency teams, rooted in collaboration with clients from the ground up. Maker Lab’s cross-functional teams of multidisciplinary specialists are embedded into client teams across digital marketing competencies — from measurement & analytics to content production. Role Summary: We’re looking for an AI Engineer for our holding company, Miroma, to support the workflows and the development of AI for our group of agencies. This role will work closely with the innovation team to deliver scalable AI solutions. Role: Design, build, test, and deploy production-grade AI solutions using Python, TypeScript/JavaScript, and cloud platforms such as Google Cloud Platform (GCP), Amazon Web Services (AWS), or Microsoft Azure. Take complete ownership of AI use cases, from initial technical design and architecture through to deployment, monitoring, and iteration. Translate ambiguous business needs into robust and scalable technical systems. Engineer complex integrations with a diverse ecosystem of modern APIs, including leading AI models, cloud data platforms, and enterprise SaaS applications across departments like Marketing, HR, Legal, and Finance. Identify and abstract common patterns to build robust, reusable components and engines. Your work will establish a foundation that accelerates future development and scales our impact across the organization. Provide critical production support by rapidly troubleshooting, debugging, and resolving integration issues and system failures to ensure high availability and performance. You: At least 3+ years of professional experience in a full-stack development role with a verifiable portfolio of shipped projects. Strong, hands-on proficiency in both Python and TypeScript/JavaScript. Experience with a major cloud provider (AWS, Azure, GCP). Hands-on experience with Google Cloud Platform (GCP), particularly serverless components like Cloud Functions and Firestore, is strongly preferred. Experience integrating a variety of third-party REST and/or GraphQL APIs, including expertise in handling complex authentication flows and data transformation. Experience with LLM API integrations (e.g., Gemini, OpenAI, Anthropic). This must include practical application of prompt engineering, function/tool calling, and parsing complex model responses. A track record of delivering complete solutions with a high degree of autonomy and minimal supervision. A mindset of quality ownership, demonstrated by writing clean, maintainable, and production-ready code. Candidates must have proven experience defining and implementing their own unit and integration tests. Familiarity with workflow automation tools is preferred. Please note: due to the high volume of applications, only successful candidates will be contacted with a follow-up introduction email. If you do not receive an email from Maker Lab, your application has been unsuccessful this time around. Look out for future roles! By submitting your application, you consent to the collection, use and disclosure of your data by the Maker Lab team for the purposes of your application. Where your application contains personal data of third parties, you confirm that you have obtained all necessary consents to provide the Maker Lab team with such personal data and that we may collect, use and/or disclose such data in accordance with the Personal Data Protection Act 2012.

Responsibilities

Design, build, and deploy production-grade AI solutions while managing the full technical lifecycle from architecture to monitoring. You will engineer complex integrations with modern APIs and cloud platforms to support scalable AI workflows across the organization.