Principal AI/ML Solution Architect

IQuest Solutions Corporation; Hyderabad; Vor Ort; INR 4.000.000 - 9.000.000; Vollzeit

Zusammenfassung

iQuest Solutions in Hyderabad invites a Principal AI/ML Solution Architect to lead enterprise DS, ML, GenAI, and agentic AI initiatives. You will own end-to-end architecture across problem definition, data assessment, modeling, deployment, and operations for manufacturing-focused use cases.

The role is client-facing, requires hands-on ML background, and collaboration with engineers, client architects, business stakeholders, and executives to translate complex requirements into scalable

Qualifikationen

• 12+ years of technology experience in data science, ML or AI disciplines.
• 7+ years designing and delivering ML/Data Science solutions including production-grade systems.
• 3+ years in AI/ML architecture or principal/lead engineering.
• 1+ year implementing production LLM/Generative AI and agentic AI solutions.
• Strong ML fundamentals: supervised/unsupervised learning, feature engineering, validation.
• GenAI/LLM experience: RAG, embeddings, vector search, guardrails, evaluation.
• Agentic AI experience: orchestration, tool calling, memory, multi-step workflows.
• Strong Python skills for prototyping and troubleshooting ML/GenAI implementations.
• Good MLOps/LLMOps knowledge: tracking, registries, CI/CD, Docker/Kubernetes.
• Strong AWS AI/ML stack experience: SageMaker/Bedrock, data services, observability.

Aufgaben

• Own end-to-end architecture for enterprise DS/ML/GenAI/agentic AI solutions.
• Translate problems into practical AI solutions: data, modeling, deployment, ops.
• Architect production ML systems: maintenance, anomaly detection, forecasting, CVQ.
• Guide ML approaches: feature engineering, model selection, validation, time-series.
• Design GenAI solutions using RAG, embeddings, retrieval, prompts and guardrails.
• Architect agentic AI solutions with tool calling, orchestration, memory, workflows.
• Define production ML architecture: training/inference pipelines, serving, CI/CD.
• Provide hands-on direction to Data Scientists, ML/Data Engineers, Cloud Engineers.
• Design cloud-native AWS architectures for AI workloads (SageMaker/Bedrock, S3, Glue).
• Set architecture standards, design reviews, production-quality expectations.
• Ensure scalability, security, cost efficiency, governance and observability.

Kenntnisse

Python

GenAI

LLM/GenAI

MLOps

SageMaker

Bedrock

ECS/EKS

Data Science

Communication

Tools

SageMaker

Bedrock

S3

Glue

EMR

Redshift

Kinesis

Lambda

Docker

Kubernetes

Spark

Kafka

Jobbeschreibung

Location

Hyderabad, India (Comfortable with monthly travel)

Client

iQuest Solutions

Engagement

Enterprise Data & AI

Location

Hyderabad, India (Comfortable with monthly travel)

Work Type / Hours

Contract | US Central Time (CST/CDT)

The Role

As Principal AI/ML Solution Architect, you will be the senior technical leader responsible for architecting and guiding enterprise Data Science, Machine Learning, Generative AI, and agentic AI solutions. You will work across the complete solution lifecycle from understanding business problems and assessing data to defining the ML/AI approach, architecture, implementation strategy, production deployment, and ongoing operations. This role requires a strong hands‑on background in Data Science and ML combined with architecture and technical leadership experience. The ideal candidate has personally built and delivered production ML systems before moving into broader AI/ML architecture responsibilities, and has recent practical experience implementing LLM/GenAI and agentic AI solutions. The role is client‑facing and requires the ability to work with engineering teams, client architects, business stakeholders, and executives to convert complex or ambiguous requirements into scalable production solutions.

Key Responsibilities

• Own end-to-end architecture for enterprise Data Science, ML, Generative AI, and agentic AI solutions across business and manufacturing use cases.
• Translate business problems into practical AI solutions covering use-case definition, data assessment, modeling approach, architecture, implementation, deployment, monitoring, and continuous improvement.
• Architect production ML systems including predictive maintenance, anomaly detection, forecasting, computer-vision quality inspection, and process optimization.
• Guide ML/Data Science approaches including feature engineering, model selection, validation, experimentation, classical ML, time-series methods, and deep learning where appropriate.
• Design enterprise GenAI solutions using RAG, embeddings/vector search, retrieval strategies, prompt/context engineering, LLM evaluation, guardrails, observability, and LLMOps.
• Architect agentic AI solutions using tool/function calling, orchestration, state and memory, multi-step workflows, human-in-the-loop patterns, and API/MCP integrations.
• Define production ML architecture including training and inference pipelines, model serving, monitoring, drift detection, retraining, model lifecycle management, and CI/CD.
• Provide hands-on technical direction to Data Scientists, ML Engineers, GenAI/Agentic AI Engineers, Data Engineers, and Cloud Engineers; review solution designs, modeling approaches, and critical implementations.
• Design cloud-native AWS architectures for AI/ML workloads using SageMaker, Bedrock, S3, Glue, EMR, Redshift, Kinesis/MSK, Lambda, ECS/EKS, IAM, and related services as appropriate.
• Establish architecture standards, design reviews, technology decisions, evaluation practices, and production-quality expectations for AI/ML delivery.
• Ensure solutions meet enterprise requirements for scalability, reliability, security, cost efficiency, governance, observability, and maintainability.
• Serve as a senior technical advisor to client architects, IT/OT teams, business leaders, and executive stakeholders; clearly communicate architecture decisions, trade-offs, risks, and progress.

Required Qualifications

• 12+ years of overall technology experience with significant experience in Data Science, ML Engineering, AI Engineering, or related disciplines.
• 7+ years of direct experience designing, building, and delivering ML/Data Science solutions, including production-grade systems not only proofs of concept.
• 3+ years in AI/ML architecture, solution architecture, principal/lead engineering, or an equivalent technical leadership role.
• At least 1+ year of direct project experience implementing production LLM/Generative AI and agentic AI solutions.
• Strong ML/Data Science fundamentals including supervised/unsupervised learning, feature engineering, model selection and validation, experimentation, forecasting/time-series, and deep learning where relevant.
• Strong GenAI/LLM experience including RAG, embeddings, vector search/databases, retrieval design, prompt/context engineering, LLM evaluation, guardrails, and production LLM application patterns.
• Practical agentic AI experience including orchestration frameworks, tool/function calling, state/memory, multi-step workflows, API or MCP integrations, human-in-the-loop patterns, and agent evaluation.
• Strong Python skills with the ability to understand, review, prototype, and troubleshoot ML/GenAI implementations not only define high-level architecture.
• Good understanding of MLOps/LLMOps including experiment tracking, model registries, deployment, monitoring, drift detection, retraining, CI/CD, Docker/Kubernetes, and model lifecycle management.
• Strong AWS architecture experience for AI/ML workloads, particularly SageMaker and/or Bedrock along with supporting data, compute, integration, security, and observability services.
• Strong communication and client-facing skills with the ability to translate business requirements into technical AI/ML solutions and explain complex decisions to both engineers and executives.

Preferred Qualifications

• Industrial/manufacturing AI experience such as predictive maintenance, anomaly detection, computer vision, process optimization, digital twins, or supply-chain forecasting.
• Prior consulting, systems integrator, or professional services experience with client-facing enterprise delivery.
• Experience with modern data platforms and technologies such as Spark, Kafka/Kinesis, Airflow, Databricks, Snowflake, Redshift, Delta/Iceberg, or equivalent.
• Exposure to edge ML/AI deployment, particularly in manufacturing or plant environments.
• Familiarity with enterprise AI/data governance, security, privacy, and compliance.
• AWS Professional-level or relevant AI/ML/cloud certifications are a plus.

Candidate Profile

We are specifically looking for an AI/ML architect with strong roots in hands‑on Data Science and Machine Learning. Candidates whose experience is primarily traditional cloud/data solution architecture with only high‑level oversight or limited exposure to ML, GenAI, or agentic AI are unlikely to be a fit. Candidates should be able to discuss specific production ML and AI systems they have personally designed or delivered and explain the technical decisions behind them.

Engagement Details

This is a Contract position based in Hyderabad, India. The candidate must be comfortable working in the US Central Time Zone to support the client.