Technical Architect -AI/ML

We are looking for a visionary yet hands-on AI Solution Architect who thrives at the intersection of technology, business, and innovation. This is a client-facing leadership role for someone who can conceptualize, design, and deliver robust AI-driven applications while staying ahead of the curve with emerging AI trends and technologies. You will be responsible for the entire lifecycle of AI solution development – from client discussions and requirements analysis to architecture design, algorithm selection, solution development, team guidance, and successful delivery. 

Job Location:

Key Responsibilities: 

• Client Engagement & Consulting

Interact directly with clients and stakeholders to understand complex business problems.

Translate business needs into AI/ML opportunities and articulate solution strategies clearly.

Present solution architectures, effort estimates, timelines, and potential ROI.

• Solution Design & Architecture

 Define end-to-end AI architecture including data pipelines, model selection, AI engines, integration layers, APIs, and deployment strategies.

Make informed choices of AI/ML/DL algorithms, frameworks, and platforms based on problem type and constraints.

Ensure the architecture is scalable, modular, secure, and optimized for performance.

• Hands-On Development

 Develop critical components or proof-of-concepts when needed.

 Perform hands-on design and coding for pipelines, model training, inferencing, or integrations.

 Create reusable components and automation scripts for repeatability.

• Team Leadership & Delivery Oversight

 Build and mentor a high-performing AI development team.

 Drive agile development cycles, ensuring timely and quality delivery.

 Collaborate with DevOps, Product Managers, and QA teams throughout SDLC.

• AI/ML/DL Expertise:

o Proven experience with supervised, unsupervised, and reinforcement learning.

o Deep knowledge of ML algorithms (e.g., XGBoost, SVM, Random Forest) and DL architectures (CNNs, RNNs, Transformers, LLMs).

o Hands-on with Python, PyTorch, TensorFlow, Keras, Scikit-learn, Hugging Face, etc.

• Architecture & System Design:

o Strong grasp on designing large-scale AI/ML pipelines using microservices, APIs, and cloud-native architecture.

o Experience designing MLOps workflows (CI/CD for ML) using tools like MLflow, Kubeflow, Airflow, DVC.

• Cloud & Platforms:

o Proficient in AWS/GCP/Azure AI/ML services (e.g., SageMaker, Vertex AI, Azure ML Studio).

o Familiarity with vector databases (e.g., FAISS, Pinecone), model versioning, and deployment strategies (e.g., REST APIs, gRPC, containers, Kubernetes).

• Data Engineering:

o Working knowledge of data wrangling, pre-processing, ETL, feature engineering, data versioning.

o Tools: Spark, Pandas, Snowflake, Kafka, Databricks, Delta Lake.

• Product & Project Ownership:

o Ability to estimate efforts, manage scope, and align delivery with client expectations.

o Experience in productizing AI models and integrating them into full-stack applications.

• Soft Skills:

o Excellent communication, stakeholder management, and presentation skills.

o Ability to simplify complex AI concepts for non-technical stakeholders.

Preferred/Nice-to-Have:

o Experience with Generative AI (LLMs, GPT, BERT, Stable Diffusion, LangChain, RAG, etc.)

o Knowledge of Prompt Engineering, Fine-Tuning, and RLHF

o Experience in NLP, Computer Vision, Time Series, or Recommendation Engines

o Understanding of ethical AI, explainable AI, and compliance in AI systems

o Publications, contributions to open-source, or AI certifications

Education:

o Bachelor’s or Master’s degree in Computer Science, Data Science, AI, or related fields.

o Certifications in Cloud AI/ML platforms or advanced AI specializations are a plus.