
Strategic AI Solutions Architect
4 days ago
We are seeking a Senior AI Engineer to lead the development and deployment of cutting-edge AI systems with a strong focus on large language models (LLMs), retrieval-augmented generation (RAG), AI agents, and intelligent automation.
You will work closely with cross-functional teams to translate business needs into AI solutions, bringing your expertise in building scalable ML infrastructure, deploying models in production, and staying at the forefront of AI innovation.
Main ResponsibilitiesAI & ML System Development:
- Design, develop, and optimize end-to-end ML models using LLMs, transformer architectures, and custom RAG frameworks.
- Fine-tune and evaluate generative and NLP models for business-specific applications such as conversational flows, auto-replies, and intelligent routing.
- Lead prompt engineering and build autonomous AI agents capable of executing multi-step reasoning.
Infrastructure, Deployment & MLOps:
- Architect and automate scalable training, validation, and deployment pipelines using tools like MLflow, SageMaker, or Vertex AI.
- Integrate ML models with APIs, databases (vector/graph), and production services ensuring performance, reliability, and traceability.
- Monitor model performance in real-time, and implement A/B testing, drift detection, and re-training pipelines.
Data & Feature Engineering:
- Work with structured, unstructured, and semi-structured data (text, embeddings, chat history).
- Build and manage vector databases (e.g., Pinecone, Weaviate) and graph-based retrieval systems.
- Ensure high-quality data ingestion, feature pipelines, and scalable pre-processing workflows.
Team Collaboration & Technical Leadership:
- Collaborate with product managers, software engineers, and stakeholders to align AI roadmaps with product goals.
- Mentor junior engineers and establish best practices in experimentation, reproducibility, and deployment.
- Stay updated on the latest in AI/ML (LLMs, diffusion models, multi-modal learning), and drive innovation in applied use cases.
Essential Qualifications:
- Bachelor's/Master's degree in Computer Science, Engineering, AI/ML, or a related field from a Tier 1 institution.
- 2+ years of experience building and deploying machine learning models in production.
- Expertise in Python and known the frameworks like TensorFlow, PyTorch, Hugging Face, Scikit-learn.
- Hands-on experience with transformer models, LLMs, LangChain, LangGraph, OpenAI API, or similar.
- Deep knowledge of machine learning algorithms, model evaluation, hyperparameter tuning, and optimization.
- Experience working with cloud platforms (AWS, GCP, or Azure) and ML Ops tools (MLflow, Airflow, Kubernetes).
- Strong understanding of SQL, data engineering concepts, and working with large-scale datasets.
Preferred Qualifications:
- Experience with prompt tuning, agentic AI systems, or multi-modal learning.
- Familiarity with vector search systems (e.g., Pinecone, FAISS, Milvus) and knowledge graphs.
- Contributions to open-source AI/ML projects or publications in AI journals/conferences.
- Experience in building conversational AI or smart assistants using WhatsApp or similar messaging APIs.
About this role:
- Build AI that directly powers growth for 100,000+ businesses.
- Work on cutting-edge technologies like LLMs, RAG, and AI agents in real production environments.
- High ownership, fast iterations, and impact-focused work.
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