Location: Hyderabad, India, Hybrid

Employment Type: Full-time

Experience: 8–12 years total, with at least 4 years in architecture roles and 2+ years building AI/ML solutions in production

Compensation: ₹32–48 LPA fixed

About Assentcode Technologies

Assentcode Technologies is a Hyderabad-based software services company, founded in 2019 by a group of entrepreneurial engineers. We help businesses across the globe build, modernize, and scale their technology, with offices in Hyderabad and Frisco, Texas (USA).

Our core services include

- Product Engineering (product design and development, web and mobile apps, UI/UX)
- Data Analytics, AI/ML, chatbots, and virtual assistants
- Cloud solutions, DevOps, and CI/CD
- Legacy modernization and digital transformation
- Custom enterprise software and quality engineering

We are a lean, fast-moving team, and AI is one of our biggest growth areas. We are looking for an enterprise architect who can turn a client's business problem into a well-designed, production-grade AI solution.

About the Role

As our Enterprise AI Architect, you will own the technical design of AI products and solutions for our enterprise clients, from the first discovery conversation to production architecture. You will decide what to build, which models and patterns to use, how it integrates with the client's systems, and how it stays secure, reliable, and cost-effective at scale. This is a hands-on architecture role: you will define the blueprint, guide the delivery team, and stay close enough to the code to validate that what's built matches what was designed.

You will also work closely with our business development team as the technical voice in client conversations, so you should be comfortable explaining complex AI concepts to both engineers and executives.

What You Will Own

Client Problem → Discovery → Solution Architecture → Proof of Concept → Estimation and Proposal → Delivery Guidance → Production Readiness → Continuous Improvement

Key Responsibilities

Solution Design and Architecture

- Translate business problems into AI solution architectures, including GenAI/LLM applications, RAG systems, AI agents, predictive models, and intelligent automation
- Select the right approach for each problem: build vs. buy, open-source vs. proprietary models, fine-tuning vs. RAG vs. prompt engineering, and when AI is not the right answer
- Design end-to-end architectures covering data ingestion, vector stores, model serving, orchestration, APIs, integration with enterprise systems, and user-facing applications
- Create architecture documents, solution blueprints, and technical diagrams that delivery teams can build from

Client and Pre-Sales Engagement

- Join discovery workshops with CTOs, CIOs, and business leaders to understand objectives, constraints, and data readiness
- Support the business development team with technical proposals, SOW inputs,



effort estimates, and architecture presentations
- Build and demo proofs of concept to validate feasibility and win client confidence
- Present trade-offs, risks, and timelines honestly, and manage client expectations on what AI can and cannot deliver

Delivery Leadership

- Provide technical direction to engineering, data, and DevOps teams during implementation
- Review designs and code for architectural integrity, scalability, and maintainability
- Define standards for LLMOps/MLOps: CI/CD for models, monitoring, versioning, evaluation, and rollback
- Mentor engineers and help build our internal AI capability

Quality, Security, and Governance

- Establish evaluation frameworks for AI quality: accuracy, hallucination rates, latency, cost per query, and bias
- Design for data privacy, security, access control, and compliance (e.g., GDPR, SOC 2, HIPAA where relevant)
- Apply responsible AI practices, including guardrails, human-in-the-loop design, and auditability
- Optimize for performance and cloud cost without compromising reliability

Innovation and Thought Leadership

- Track the fast-moving AI landscape (models, frameworks, tools, and best practices) and decide what is ready for enterprise use
- Build reusable accelerators, reference architectures, and templates that speed up future projects
- Contribute to case studies, technical content, and our AI service positioning

Must-Have Requirements

- 8–12 years of experience in software engineering, data engineering, or ML, with at least 3 years in an architect or technical lead role
- Hands-on experience designing and delivering AI/ML solutions that reached production, with examples you can walk us through
- Strong practical experience with Generative AI: LLM integration, RAG pipelines, vector databases, prompt engineering, and agent frameworks (e.g., LangChain, LlamaIndex, or similar)
- Solid understanding of ML fundamentals and when to use classical ML vs. LLM-based approaches
- Deep experience with at least one major cloud platform (AWS, Azure, or GCP) and its AI/ML services (e.g., Bedrock, SageMaker, Azure OpenAI, Vertex AI)
- Strong software architecture skills: microservices, APIs, event-driven design, data pipelines, and system integration
- Strong Python skills and the ability to review code and build prototypes
- Experience with MLOps/LLMOps: model deployment, monitoring, evaluation, and CI/CD
- Understanding of data architecture, including data lakes, warehouses, ETL/ELT, and data quality
- Knowledge of security, privacy,



and governance requirements for enterprise AI
- Excellent communication skills: able to explain architecture to executives and engineers alike
- Experience working with international clients and distributed teams

Valuable to Have

- Experience in a services, consulting, or multi-client environment
- Pre-sales or solutioning experience, including proposals, estimates, and client presentations
- Experience fine-tuning or evaluating open-source models (Llama, Mistral, etc.) and deploying them on your own infrastructure
- Familiarity with tools such as MLflow, Kubeflow, Airflow, Docker, Kubernetes, and Terraform
- Exposure to legacy modernization or integrating AI into existing enterprise applications
- Cloud architecture certifications (AWS, Azure, or GCP) or AI/ML specializations
- Contributions to open-source projects, published content, or conference talks
- Bachelor's or Master's degree in Computer Science, Data Science, or a related field

This Role May Not Be a Fit If You…

- Have worked only on research, notebooks, or proofs of concept that never reached production
- Have only used AI through no-code tools or API wrappers, without architectural depth
- Prefer a purely advisory role with no involvement in implementation
- Are not comfortable engaging directly with clients and business stakeholders
- Want a large, highly structured organization with a fully defined process

How Success Will Be Measured

- Quality and clarity of architectures and solution designs delivered
- Technical contribution to proposals won and client confidence in pre-sales
- Successful delivery of AI projects to production, on time and within scope
- Reliability, performance, and cost-efficiency of deployed AI solutions
- Reusable accelerators and reference architectures created
- Growth in the team's AI capability through mentoring and standards

Compensation and Benefits

- Fixed salary of ₹32–48 LPA, based on experience and depth of AI delivery
- Performance-linked bonus tied to project outcomes and pre-sales contribution
- Direct access to founders and leadership, with real influence on our AI strategy and service offerings
- The chance to shape architecture standards and build our AI practice from the ground up
- Exposure to enterprise clients and our US office
- Learning support for cloud and AI certifications
- Statutory advantages (PF, gratuity) and health insurance
- A growth path toward Head of AI / Principal Architect / Chief Technology Officer-track roles

How to Apply

Apply through LinkedIn or email your resume to [email protected] with the subject line "Enterprise AI Architect". To help us evaluate quickly, please include a short description (or link) of one AI solution you architected that went to production: the business problem, your architecture choices, the stack, and the outcome.

Learn more about us: www.assentcode.tech

📌 Enterprise AI Architect - AI Product Design & Solutioning (Hyderabad)
🏢 Assentcode Technologies
📍 Hyderabad