Job Description & How to Apply Below
AI Integrations Engineer
Location:
Gurugram, Haryana
Duration:
Long-Term Contract
Company Overview:
Fluidech is a technology consulting and managed services firm focused on cybersecurity.
Founded in 2014 and headquartered in Gurugram —and today with a client base spanning over 100 organisations worldwide —Fluidech designs IT solutions aligned with business objectives, fostering trusted relationships and delivering measurable performance improvements.
Established as a born-in-the-cloud company, Fluidech has evolved into a trusted technology partner that helps businesses build ( Cloud & Infrastructure), automate (Dev Ops), and secure (Cyber Security services).
Our solutions span diverse industry verticals, aligned with each client’s business goals.
In addition to holding ISO 9001 and ISO 27001 certifications and an award-winning cybersecurity team, the company has a strong value proposition in its GRC services across frameworks, including but not limited to NCIIPC’s CAF, SEBI’s CSCRF , and others.
Position Overview:
We are seeking an AI Integrations Engineer to design, build, and maintain integrations between AI models, platforms, and our internal/external systems. This role sits at the intersection of software engineering, APIs, and applied AI, enabling real-world deployment of AI capabilities across products and workflows.
You will work closely with product managers, data scientists, and engineering teams to ope rationalise AI solutions and ensure they are scalable, secure, and reliable.
Key Responsibilities:
Design, develop, and maintain AI-powered integrations across internal systems, third-party platforms, and cloud services
Integrate LLMs and AI services (e.g., OpenAI, Azure AI, AWS AI, Google AI) via APIs and SDKs
Build and manage REST/Graph
QL APIs, webhooks, and event-driven architectures
Deploy AI workflows into production, ensuring performance, reliability, and observability
Monitor AI integrations for latency, errors, and cost efficiency
Troubleshoot and resolve integration and deployment issues
Required:
Bachelor’s degree in computer science, Engineering, or equivalent practical experience
5+ years of experience in software engineering or integrations engineering
Strong experience in Python, JavaScript/Type Script, or Java
Core AI/ML knowledge (algorithms, deep learning, NLP)
Hands-on experience with API design, consumption, and integration
Experience integrating AI/ML or LLM-based services into production systems
Strong experience with cloud platforms (AWS, Azure, or GCP)
Knowledge of containerization and deployment (Docker, CI/CD pipelines)
Understanding of data formats and messaging (JSON, REST, webhooks, queues)
Preferred:
Experience with prompt engineering, RAG pipelines, or AI agents
Familiarity with vector databases (Pinecone, Weaviate, FAISS, Milvus)
Experience with MLOps or AI observability tools
Exposure to enterprise integrations (CRM, ERP, SaaS platforms)
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