Position - AI ML Engineer
Experience: 7+ years in Python development with proven experience in AI and productivity tooling
Work mode: Remote
Immediate joiners preferred
Number of Openings: 1
Working hours : 2 PM - 12 AM IST
Job Summary
We are seeking a Senior Python Developer who excels at building scalable, AI-integrated systems using modern tools and frameworks. The ideal candidate embraces AI-assisted development (GitHub Copilot, ChatGPT, AutoGen, etc.) to boost productivity, improve code quality, and drive innovation across our application stack. This role combines backend expertise, cloud-native architecture, and hands-on AI integration to deliver intelligent, high-performance solutions.
Key Responsibilities
AI Model Integration & Optimization
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Integrate APIs from multiple AI platforms (OpenAI, Anthropic, Gemini, Llama, Mistral, etc.) into scalable backend systems.
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Build multi-model orchestration layers balancing cost, latency, and accuracy.
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Fine-tune prompts, manage context windows, and implement RAG (Retrieval-Augmented Generation) solutions for domain-specific use cases.
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Optimize token usage, caching, and filtering strategies to enhance system efficiency and user experience.
Application & System Development
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Design and implement AI-enabled workflows seamlessly integrated with web, mobile, or enterprise ecosystems.
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Develop Python-based backends and APIs using frameworks like FastAPI, Flask, or Django.
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Build and deploy microservices and cloud-native services leveraging Docker, Kubernetes, and serverless architectures
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Collaborate with frontend, DevOps, and product teams to ensure smooth feature delivery and deployment.
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Monitor and evaluate AI responses through metrics, evaluation frameworks, or RLHF-inspired feedback loops.
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Implement AI guardrails for responsible usage including bias detection, toxicity filtering, and compliance enforcement.
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Debug and resolve performance or reliability issues in AI-powered production systems.
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Innovation & Collaboration
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Stay up to date with the evolving AI model landscape, exploring new models, APIs, and orchestration frameworks.
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Experiment with multi-modal AI (vision, text, speech) for applicability in client scenarios.
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Work closely with cross-functional teams to translate business goals into intelligent, automated features.
Primary Skills:
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Python backend expert: FastAPI, async I/O, API design, testing.
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Production LLM integration: OpenAI/Anthropic/Gemini/
Mistral; prompt and context strategies; RAG with a vector DB. -
Cloud-native delivery: Docker, AWS (preferred), CI/CD, IaC basics (Terraform or Pulumi).
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Data layer: SQL (PostgreSQL), caching/queues (Redis + Celery/RQ/SQS/Kafka).
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Daily AI-assisted development (Copilot/Others) for coding and tests.
Required Skills & Qualifications
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Expert in Python backend development with hands-on experience integrating AI models, building cloud-native microservices, and using AI-assisted coding tools for faster, smarter development.
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Proven hands-on experience integrating LLM APIs (OpenAI, Claude, Gemini, Llama, etc.).
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Strong expertise in AI/ML frameworks (TensorFlow, PyTorch, scikit-learn, Hugging Face, etc.)" as essential qualification
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Practical knowledge of LangChain, LlamaIndex, Codium or similar frameworks for AI workflow orchestration.
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Understanding of prompt engineering, embeddings, vector databases (Pinecone, Weaviate, FAISS, pgvector), and RAG pipelines.
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Strong background in cloud platforms (AWS, GCP, Azure), containerization, and orchestration.
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Deep understanding of REST/GraphQL APIs, async programming, task queues, and caching mechanisms.
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Familiarity with SQL/NoSQL databases (PostgreSQL, MongoDB, Redis).
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Experience using AI-assisted tools such as GitHub Copilot, ChatGPT API, AutoGen, or OpenDevin for coding and testing automation.
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Exposure to CI/CD pipelines and Infrastructure as Code (Terraform, Pulumi).
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Knowledge of data preprocessing, NLP/NLU, and model evaluation techniques.
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Data Engineering & Processing, Data pipeline development , ETL/ELT processes, Batch processing and stream processing frameworks, Large-scale data handling with pandas, NumPy, Dask
Preferred Skills
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Hands-on with multi-modal AI (vision, text-to-speech, speech-to-text).
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Experience with MLOps practices including CI/CD for AI pipelines, model monitoring, and drift detection.
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Background in fine-tuning, reinforcement learning, or custom model training.
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Familiarity with enterprise security standards (GDPR, HIPAA, SOC2).
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Contributions to open-source or personal AI-assisted coding initiatives.
Soft Skills
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Excellent problem-solving and analytical thinking ability.
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Strong cross-functional collaboration and communication skills.
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Clear technical documentation habits.
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Curious, experimental mindset with a drive to explore the next frontier in AI-driven development.

