Responsibilities

<ul>
<li>Understand the values and vision of the organization</li>
</ul>

<ul>
<li>Protect the Intellectual Property</li>
</ul>

<ul>
<li>Adhere to all the policies and procedures</li>
</ul>

<ul>
<li>Lead the design, development, and implementation of AI-powered solutions, ensuring alignment with client requirements and business objectives.</li>
</ul>

<ul>
<li>Lead the AI solution lifecycle, from concept to deployment, ensuring that milestones and deadlines are met.</li>
</ul>

<ul>
<li>Lead architecture reviews and act as the technical design authority for AI initiatives.</li>
</ul>

<ul>
<li>Drive MLOps adoption, including model governance, monitoring, automation, and lifecycle management.</li>
</ul>

<ul>
<li>Evaluate and optimize AI workloads for performance, latency, scalability, and cost-efficiency.</li>
</ul>

<ul>
<li>Work closely with CXO-level stakeholders to translate business needs into enterprise AI solutions.</li>
</ul>

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

<ul>
<li>Collaborate with clients, product managers, and technical teams to understand business challenges and translate them into AI-driven solutions.</li>
</ul>

<ul>
<li>Design end-to-end AI architectures, including data pipelines, model selection, deployment strategies, and performance monitoring.</li>
</ul>

<ul>
<li>Oversee the integration of AI models into production environments, ensuring that they deliver consistent, high-quality results.</li>
</ul>

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

<ul>
<li>Evaluate and select appropriate AI tools, frameworks, and technologies for specific project requirements.</li>
</ul>

<ul>
<li>Provide technical leadership and mentorship to junior AI engineers and data scientists.</li>
</ul>

<ul>
<li>Ensure that AI models are tested thoroughly, validated, and optimised for performance, accuracy, and scalability.</li>
</ul>

<ul>
<li>Develop AI roadmaps and ensure alignment with long-term business and technology strategy.</li>
</ul>

<ul>
<li>Stay current with the latest advancements in AI technologies and contribute to the ongoing development of AI solutions and frameworks within the organization.</li>
</ul>

<ul>
<li>Communicate the technical aspects of AI solutions clearly to both technical and non-technical stakeholders.</li>
</ul>

Requirements

Essential Skills

<ul>
<li>Expertise in designing AI architectures and solutions for complex business problems.</li>
</ul>

<ul>
<li>Hands-on experience with Generative and Agentic AI, LLM fine-tuning, Agentic/RAG architecture, and embedding models.</li>
</ul>

<ul>
<li>Strong expertise in MLOps platforms such as MLflow, Kubeflow, SageMaker, Bedrock, Foundry or Vertex AI.</li>
</ul>

<ul>
<li>Ability to influence senior stakeholders and lead cross-functional technical discussions at an enterprise level.</li>
</ul>

<ul>
<li>Deep understanding of machine learning, deep learning, NLP, and computer vision algorithms and their application to real-world problems.</li>
</ul>

<ul>
<li>Strong experience in working with data pipelines, data storage, and processing technologies.</li>
</ul>

<ul>
<li>Ability to lead and guide a team of AI engineers and data scientists to build scalable AI solutions.</li>
</ul>

<ul>
<li>Experience with performance optimization, model evaluation, and continuous improvement of AI systems.</li>
</ul>

<ul>
<li>Extensive experience with AI frameworks and tools such as TensorFlow, PyTorch, Keras, Scikit- learn and others.</li>
</ul>

Personal

<ul>
<li>Demonstrate proactive thinking</li>
</ul>

<ul>
<li>Should have strong interpersonal relations, expert business acumen and mentoring skills</li>
</ul>

<ul>
<li>Strong problem-solving skills with attention to detail.</li>
</ul>

<ul>
<li>Have the ability to work under stringent deadlines and demanding client conditions</li>
</ul>

Preferred Skills

<ul>
<li>Excellent understanding of AI concepts, including supervised and unsupervised learning, reinforcement learning, model training, evaluation, and optimization.</li>
</ul>

<ul>
<li>Experience with vector databases (FAISS, Pinecone, Weaviate, Chroma, etc.)</li>
</ul>

<ul>
<li>Exposure to model governance, responsible AI frameworks, and compliance standards.</li>
</ul>

<ul>
<li>Cloud certifications (AWS/Azure/GCP Architect or ML Specialty) are a strong plus.</li>
</ul>

<ul>
<li>Experience with Big Data technologies such as Hadoop, Spark, and Kafka, and working with large datasets.</li>
</ul>

<ul>
<li>Strong programming skills in Python, Java, C# or similar languages, with hands-on experience in machine learning libraries.</li>
</ul>

<ul>
<li>Proficiency in cloud-based AI deployment and orchestration tools.</li>
</ul>

<ul>
<li>Ability to stay ahead of industry trends and continuously evaluate new tools, frameworks, and techniques.</li>
</ul>

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

<ul>
<li>Familiarity with DevOps practices for AI, including continuous integration and deployment pipelines for machine learning models.</li>
</ul>

Personal

<ul>
<li>Demonstrate proactive thinking</li>
</ul>

<ul>
<li>Should have strong interpersonal relations, expert business acumen, and mentoring skills</li>
</ul>

<ul>
<li>Strong problem-solving skills with attention to detail.</li>
</ul>

<ul>
<li>Have the ability to work under stringent deadlines and demanding client conditions.</li>
</ul>

Other Relevant Information

<ul>
<li>Bachelor’s degree in Computer Science, Information Technology, or a related field.</li>
</ul>

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

<ul>
<li>Proven experience in designing and implementing AI solutions in production environments, including machine learning, NLP, computer vision, and deep learning.</li>
</ul>

Solutions Architect

India

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 an

Solutions Architect · Gurugram

Job highlights

Skillset required

Job Description

Job Description for Solutions Architect

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