Senior AI/ML & Emerging Technology Solutions Architect - R&D

Job highlights

• 7+ years in AI/ML with expertise in Generative AI, Agentic AI, RF signal processing, Edge AI, and distributed systems
• Lead research, design end-to-end AI/ML and sensor-integrated architectures, develop PoCs, validate emerging tech, and provide technical leadership

Senior AI/ML & Emerging Technology Solutions Architect R&D

Location: India
Employment Type: Full-Time
Department: AI / Research & Development

Position Overview

We are seeking an experienced Senior AI/ML & Emerging Technology Solutions Architect R&D to lead research, solution architecture, technical feasibility, proof-of-concept development, and validation of advanced technology solutions.

This role goes beyond traditional AI/ML architecture and requires broad technical knowledge across Artificial Intelligence, Machine Learning, Generative AI, Agentic AI, autonomous systems, sensors, IoT, RF/signal processing, edge computing, distributed systems, networking, cybersecurity, cloud, and real-time intelligent systems.

The ideal candidate can take an unfamiliar technical problem, quickly understand the requirements, research applicable technologies, develop a differentiated solution concept, design the architecture, and define a practical PoC and validation strategy.

Innovation Lifecycle

Problem / Requirement Research Technology Assessment Solution Concept System Architecture PoC / Experiment Validation Prototype Maturation

Key Responsibilities

• Analyze complex and unfamiliar technical problems and translate requirements into practical solution concepts and system architectures.
• Design end-to-end AI/ML architectures involving Machine Learning, Deep Learning, Generative AI, LLMs, RAG, Agentic AI, multi-agent systems, Reinforcement Learning, Computer Vision, multimodal AI, predictive analytics, and autonomous decision systems.
• Architect integrated solutions involving sensors, IoT, radar, LiDAR, EO/IR, telemetry, signal processing, real-time data ingestion, sensor fusion, AI/ML processing, and automated decision-making.
• Design solutions involving RF and signal processing, including Software Defined Radio (SDR), spectrum analysis, signal classification, waveform analysis, interference detection, and RF anomaly detection.
• Architect Edge AI and distributed computing solutions for real-time inference under constrained compute, power, bandwidth, latency, or connectivity conditions.
• Design mesh, peer-to-peer, and distributed network architectures supporting dynamic nodes, sensors, intelligent devices, and autonomous platforms.
• Develop autonomous and multi-agent architectures supporting perception, reasoning,planning, coordination, action, feedback, human-machine teaming, and runtime assurance.
• Integrate heterogeneous streaming, spatial, temporal, sensor, RF, cybersecurity, and enterprise data using data fusion, knowledge graphs, multimodal processing, and event correlation.
• Determine when to use AI/ML, Generative AI, signal processing, deterministic algorithms, optimization, simulation, control systems, or hybrid approaches.
• Lead PoCs, experiments, simulations, benchmarking, and prototype development, including datasets, algorithms, hardware/software components, performance metrics, and validation criteria.
• Design architectures across cloud, edge, device, and sensor environments using APIs, microservices, containers, event streaming, message brokers, MLOps, CI/CD, cybersecurity, and observability.
• Research emerging technologies including Agentic AI, collaborative autonomy, Edge AI, distributed AI, RF AI/ML, intelligent sensing, digital twins, synthetic data, federated learning, mesh networking, autonomous cyber defense, and AI assurance.
• Evaluate AI systems for accuracy, robustness, latency, throughput, resource utilization, reliability, security, scalability, explainability, and overall system effectiveness.
• Develop architecture documents, AI/ML pipelines, data flows, agentic workflows, experiment plans, technical roadmaps, prototype designs, and technical documentation.
• Provide technical leadership to multidisciplinary teams including AI/ML engineers, data scientists, software developers, cloud engineers, networking specialists, cybersecurity professionals, sensor/hardware SMEs, and research teams.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a related technical field.
• 7+ years of overall technology experience, with significant experience in AI/ML, data science, or intelligent systems.
• Strong experience designing and architecting end-to-end AI/ML solutions.
• Strong understanding of machine learning and deep learning algorithms, model development, training, evaluation, optimization, and deployment.
• Hands-on experience with Python and AI/ML frameworks such as PyTorch, TensorFlow, Scikit-learn, Hugging Face, or equivalent.
• Experience with Generative AI, LLMs, RAG, embeddings, vector databases, prompt engineering, fine-tuning, and AI agents/agentic workflows.
• Ability to research unfamiliar technical problems and rapidly develop technically credible solution approaches.
• Experience with technical feasibility assessments, PoCs, prototypes, experiments, and performance evaluation.
• Strong understanding of data engineering and the AI/ML data lifecycle.
• Experience or familiarity with AWS, Azure, or Google Cloud AI/ML platforms.
• Understanding of APIs, microservices, containers, MLOps, CI/CD, and production AI deployment.
• Strong analytical, problem-solving, technical writing, and communication skills.

Preferred Qualifications

• Master's or Ph.D. with a research focus in AI/ML, Computer Science, Data Science, Robotics, or a related field.
• R&D, innovation lab, advanced engineering, product research, or technology consulting experience.
• Experience with Computer Vision, NLP, signal/sensor analytics, autonomous systems, predictive analytics, optimization, or multimodal AI.
• Experience translating academic research and emerging technologies into practical solutions.
• Experience developing AI solutions for edge, real-time, resource-constrained, or disconnected/degraded environments.
• Knowledge of cybersecurity considerations for AI/ML systems.
• Experience with Responsible AI, explainability, model validation, and AI governance.
• Publications,patents, open-source contributions, or demonstrated R&D/prototyping experience.

Key Skills

AI/ML Architecture, AI/ML, Machine Learning, Deep Learning, Python, PyTorch, TensorFlow, Scikit-learn, Hugging Face, Generative AI, LLM, RAG, Vector Database, Embeddings, Prompt Engineering, AI Agents, Agentic AI, Reinforcement Learning, Computer Vision, NLP, Multimodal AI, Autonomous Systems, Sensor Fusion, IoT, RF, Signal Processing, SDR, Edge AI, Edge Computing, Distributed Computing, Mesh Networks, Cloud, AWS, Azure, GCP, MLOps, Kubernetes, Docker, Microservices, APIs, Real-Time Data Processing, Data Engineering, Data Fusion, Knowledge Graphs, Digital Twins, Simulation, Federated Learning, AI Cybersecurity, Responsible AI, PoC, Prototyping, Technical Architecture, R&D, Emerging Technologies.

What We Are Looking For

We are looking for a candidate who is more than an AI developer and more than a traditional Solution Architect.

The ideal candidate should be comfortable working across multiple technical domains, including:

AI/ML + Generative AI + Agentic AI + RF + Sensors + Edge Computing + Networking + Cybersecurity + Autonomous Systems

The candidate should be able to work independently on complex and unfamiliar technical challenges, conduct research, engage domain SMEs when required, develop solution architectures, build or guide PoCs, and validate whether emerging technologies can be translated into practical solutions.