Solutions Architect · Gurugram

Responsibilities

• Understand the values and vision of the organization

• Protect the Intellectual Property

• Adhere to all the policies and procedures

• Lead the design, development, and implementation of AI-powered solutions, ensuring alignment with client requirements and business objectives.

• Lead the AI solution lifecycle, from concept to deployment, ensuring that milestones and deadlines are met.

• Lead architecture reviews and act as the technical design authority for AI initiatives.

• Drive MLOps adoption, including model governance, monitoring, automation, and lifecycle management.

• Evaluate and optimize AI workloads for performance, latency, scalability, and cost-efficiency.

• Work closely with CXO-level stakeholders to translate business needs into enterprise AI solutions.

• Work closely with cross-functional teams, including data engineers, business analysts, and UX/UI designers, to deliver end-to-end AI solutions.

• Collaborate with clients, product managers, and technical teams to understand business challenges and translate them into AI-driven solutions.

• Design end-to-end AI architectures, including data pipelines, model selection, deployment strategies, and performance monitoring.

• Oversee the integration of AI models into production environments, ensuring that they deliver consistent, high-quality results.

• Guide the adoption of best practices in AI, machine learning, and data science, ensuring that solutions are scalable, efficient, and cost-effective.

• Evaluate and select appropriate AI tools, frameworks, and technologies for specific project requirements.

• Provide technical leadership and mentorship to junior AI engineers and data scientists.

• Ensure that AI models are tested thoroughly, validated, and optimised for performance, accuracy, and scalability.

• Develop AI roadmaps and ensure alignment with long-term business and technology strategy.

• Stay current with the latest advancements in AI technologies and contribute to the ongoing development of AI solutions and frameworks within the organization.

• Communicate the technical aspects of AI solutions clearly to both technical and non-technical stakeholders.

Requirements

Essential Skills

• Expertise in designing AI architectures and solutions for complex business problems.

• Hands-on experience with Generative and Agentic AI, LLM fine-tuning, Agentic/RAG architecture, and embedding models.

• Strong expertise in MLOps platforms such as MLflow, Kubeflow, SageMaker, Bedrock, Foundry or Vertex AI.

• Ability to influence senior stakeholders and lead cross-functional technical discussions at an enterprise level.

• Deep understanding of machine learning, deep learning, NLP, and computer vision algorithms and their application to real-world problems.

• Strong experience in working with data pipelines, data storage, and processing technologies.

• Ability to lead and guide a team of AI engineers and data scientists to build scalable AI solutions.

• Experience with performance optimization, model evaluation, and continuous improvement of AI systems.

• Extensive experience with AI frameworks and tools such as TensorFlow, PyTorch, Keras, Scikit- learn and others.

Personal

• Demonstrate proactive thinking

• Should have strong interpersonal relations, expert business acumen and mentoring skills

• Strong problem-solving skills with attention to detail.

• Have the ability to work under stringent deadlines and demanding client conditions

Preferred Skills

• Excellent understanding of AI concepts, including supervised and unsupervised learning, reinforcement learning, model training, evaluation, and optimization.

• Experience with vector databases (FAISS, Pinecone, Weaviate, Chroma, etc.)

• Exposure to model governance, responsible AI frameworks, and compliance standards.

• Cloud certifications (AWS/Azure/GCP Architect or ML Specialty) are a strong plus.

• Experience with Big Data technologies such as Hadoop, Spark, and Kafka, and working with large datasets.

• Strong programming skills in Python, Java, C# or similar languages, with hands-on experience in machine learning libraries.

• Proficiency in cloud-based AI deployment and orchestration tools.

• Ability to stay ahead of industry trends and continuously evaluate new tools, frameworks, and techniques.

• Strong knowledge of cloud platforms such as AWS, Azure, and/or Google Cloud, with expertise in deploying AI models at scale.

• Familiarity with DevOps practices for AI, including continuous integration and deployment pipelines for machine learning models.

Personal

• Demonstrate proactive thinking

• Should have strong interpersonal relations, expert business acumen, and mentoring skills

• Strong problem-solving skills with attention to detail.

• Have the ability to work under stringent deadlines and demanding client conditions.

Other Relevant Information

• Bachelor’s degree in Computer Science, Information Technology, or a related field.

• Over 15+ years of experience in software development, with at least 8 years in AI/ML solution architecture and design.

• Proven experience in designing and implementing AI solutions in production environments, including machine learning, NLP, computer vision, and deep learning.