32 Responsible Ai Jobs - Page 2

Job Description: Generative AI Expertise In depth knowledge of various Generative AI techniques including GANs Generative Adversarial Networks VAEs Variational Autoencoders and other relevant architectures Experience with both image and text generation is essential Conversant with Gen AI development tools like Prompt engineering Langchain Semantic Kernels Function calling Exposure to both API based and opens source LLMs based solution design Responsible AI Should have proficient knowledge in Responsible AI and Data Privacy principles to ensure ethical data handling transparency and accountability in all stages of AI development Must demonstrate a commitment to upholding privacy standards mitigating bias and fostering trust within data driven initiatives Machine Learning Mastery Profound understanding of machine learning principles algorithms and frameworks Able to design and implement models optimize performance and manage training pipelines effectively Technical Proficiency Proficiency in programming languages commonly used in AI development such as Python TensorFlow PyTorch or similar tools Experience with cloud platforms e g AWS Azure GCP and distributed computing is advantageous Architecture Design Ability to design end to end Generative AI architectures that encompass data preprocessing model selection training pipelines and deployment strategies Strong grasp of scalable reliable and efficient system design Key Responsibilities: A day in the life of an Infoscion As part of the Infosys consulting team your primary role would be to lead the engagement effort of providing high quality and value adding consulting solutions to customers at different stages from problem definition to diagnosis to solution design development and deployment You will review the proposals prepared by consultants provide guidance and analyze the solutions defined for the client business problems to identify any potential risks and issues You will identify change Management requirements and propose a structured approach to client for managing the change using multiple communication mechanisms You will also coach and create a vision for the team provide subject matter training for your focus areas motivate and inspire team members through effective and timely feedback and recognition for high performance You would be a key contributor in unit level and organizational initiatives with an objective of providing high quality value adding consulting solutions to customers adhering to the guidelines and processes of the organization If you think you fit right in to help our clients navigate their next in their digital transformation journey this is the place for you Technical Requirements: Primary skills Technology Artificial Intelligence Computer Vision Technology Big Data Natural language processing NLP Technology Machine Learning Python Technology Machine Learning TensorFlow Additional Responsibilities: Good knowledge on software configuration management systems Strong business acumen strategy and cross industry thought leadership Awareness of latest technologies and Industry trends Logical thinking and problem solving skills along with an ability to collaborate Two or three industry domain knowledge Understanding of the financial processes for various types of projects and the various pricing models available Client Interfacing skills Knowledge of SDLC and agile methodologies Project and Team management Preferred Skills: Technology->Artificial Intelligence->Computer Vision,Technology->Big Data->Natural language processing(NLP),Technology->Machine Learning->Python,Technology->Machine Learning->TensorFlow

Job Description Join our team as a Generative AI Architect in the AI Practice! We are looking for a visionary individual to lead the design, development, and deployment of cutting-edge Generative AI solutions, driving business value across our products and services. Key Responsibilities: - Lead generative AI initiatives in text, ASR, TTS & STT generation and develop AI pipelines and ML models. - Design scalable AI systems using state-of-the-art generative models like LLMs and diffusion models. - Collaborate with cross-functional teams to integrate generative AI into business workflows. - Define best practices for model lifecycle management, focusing on data preparation, training, evaluation, deployment, and monitoring. - Guide ethical AI development with a focus on fairness, interpretability, and compliance. Qualifications: - Bachelors or Masters degree in Computer Science or related field. - 7+ years of AI/ML development experience, with 2+ years in generative AI. - Hands-on experience with large language models and diffusion models. - Strong proficiency in Python and ML frameworks. - Experience with Azure, GCP, and containerization. - Familiarity with AI architecture patterns and model fine-tuning. - Knowledge of data privacy laws and AI ethics principles. Preferred: - Experience deploying GenAI applications in production. - Knowledge of vector databases and retrieval-augmented generation. - Experience with CI/CD pipelines for ML. Skills : - Generative AI,Large Language Models (LLMs),Diffusion Models,Machine Learning (ML),Artificial Intelligence (AI),Natural Language Processing (NLP),Python Programming,ML Frameworks (e.g., TensorFlow, PyTorch, Hugging Face),Azure,GCP,Ethical AI,Responsible AI,Vector Databases, RAG

Job Description Do you want to lead teams that find and exploit security vulnerabilities in Fortune 100 companies, critical infrastructure, and public sector agencies impacting millions of users? Join Securins Offensive Security Team where you'll emulate real-world attacks and oversee advanced offensive operations. We are a cross-disciplinary group of red teamers, adversarial AI researchers, and software developers dedicated to finding and fixing vulnerabilities across critical digital ecosystems. Role & responsibilities - Lead and perform advanced offensive security assessments, including Red Team operations, threat-based evaluations, and vulnerability exploitation. - Supervise and mentor a team of offensive engineers, manage task prioritization, and ensure high-quality delivery. - Execute Red Team operations on production systems, including AI platforms, using real-world adversarial tactics. - Provide strategic and technical security guidance to internal and external stakeholders. - Collaborate cross-functionally to integrate findings into enterprise detection and defense strategies. - Research and develop adversary TTPs across the full attack lifecycle. - Build tools to automate and scale offensive emulation and vulnerability discovery, utilizing AI/ML systems. - Continuously evaluate and enhance assessment methodologies and frameworks used by the team. - Contribute to the security community through publications, presentations, bug bounties, and open-source projects. Required Qualifications - 5+ years of experience in offensive security, red teaming, or penetration testing with at least 1 year in a leadership role. - Bachelors or Masters degree in Computer Science, Computer Engineering, or relevant field; or equivalent experience. - Expert knowledge of offensive security tactics, threat modeling, APT emulation, and Red Team operations. - Strong understanding of MITRE ATT&CK framework and exploitation of common vulnerabilities. - Proficiency in one or more programming/scripting languages (Python, Go, PowerShell, C/C++, etc.). - Hands-on experience with penetration testing tools such as Metasploit, Burp Suite Pro, NMAP, Nessus, etc. - Familiarity with security in cloud environments (AWS, Azure, GCP) and across Windows/Linux/macOS platforms. - Ability to clearly articulate findings to technical and executive audiences and lead mitigation efforts. - Authorization to work in the country of employment at time of hire and ongoing during employment. Preferred Qualifications - Certifications like OSCP, OSCE, OSEP, CRTO, or equivalent. - Experience with Purple Team operations and threat intelligence integration. - Track record in CTF competitions or bug bounty programs. - Reverse engineering experience or malware analysis expertise. - Exposure to Responsible AI and adversarial machine learning. - Participation in AI Village at DEFCON or similar security research events. - Publications or contributions to conferences such as AISec, NeurIPS, FAccT, or IC4. Other Requirements Ability to meet Securin, customer, and/or government security screening requirements. This includes a background check at the time of hire/transfer and every two years thereafter. Who Should Apply You have experience executing technical research and offensive security strategies with teams. You are skilled in experimental security science and confident in building your own tools. You clearly communicate findings, are mission-driven, and want to drive change in AI and cybersecurity. Role-Specific Policy This hybrid role requires in-office presence at least 50% of the time. Locations: Chennai, Tamil Nadu (India)

Job Title : AI Governance Specialist Location : Bangalore Job Title: Position Summary: We are looking for a seasoned AI Governance professional with proven experience in leading and managing enterprise-wide AI governance frameworks. This individual will be responsible for defining, implementing, and overseeing governance policies that ensure ethical, compliant, and responsible use of AI across the organization. The ideal candidate will drive the strategy to align AI initiatives with internal standards, regulatory requirements, and societal expectations. Key Responsibilities: AI Policy & Framework Development: Implement organizational AI governance policies and risk management frameworks. Align internal governance practices with global standards and regulations (e.g., EU AI Act, NIST AI RMF, ISO/IEC 42001). Collaborate with legal, compliance, data science, and product teams to ensure AI systems meet ethical and regulatory requirements. Risk Assessment & Compliance: Conduct AI risk and impact assessments across the model lifecycle. Monitor compliance with emerging AI regulations, data privacy laws (e.g., GDPR), and sector-specific requirements. Identify and escalate potential ethical, legal, or reputational risks. Ethical AI & Responsible Innovation: Promote fairness, transparency, accountability, explainability, and human oversight in AI/ML systems. Support initiatives for bias detection, algorithmic accountability, and model interpretability. Governance Operations & Tooling: Work with cross-functional teams to embed governance controls into MLOps and AI development pipelines. Evaluate or develop tools to support model documentation (e.g., model cards, datasheets), audit trails, and explainability. Stakeholder Engagement & Training: Act as a subject-matter expert on AI governance for internal and external stakeholders. Design and deliver training programs on responsible AI practices for technical and business teams. Qualifications: Education: Bachelors or Master’s degree in Law, Computer Science, Data Science, Ethics, Public Policy, or a related field. Additional certifications (e.g., in AI Ethics, Data Protection, Risk Management) are a plus. Experience: 7-12 years of experience in AI/ML, risk management, regulatory compliance, or corporate governance. Experience with responsible AI frameworks, audit processes, or regulatory readiness preferred. Skills: Deep understanding of AI/ML technologies and their societal and organizational impacts. Experience working in regulated industries (e.g., finance, healthcare, energy). Knowledge of cybersecurity, data governance, or digital ethics. Strong analytical, communication, and stakeholder management skills. Ability to navigate ambiguity and influence cross-functional teams in a fast-paced environment

Role - Consultants - AI Experience - 10 to 16 years. Location -Pan India Desired Competencies (Technical/Behavioral Competency) Must-Have Strong experience with Python and ML frameworks like TensorFlow, PyTorch, scikit-learn. Expertise in model deployment, APIs (Flask/FastAPI), and containerization (Docker, Kubernetes). Proven hands-on experience with at least one major cloud platform for AI/ML workflows. Experience with CI/CD pipelines, MLflow, or Kubeflow. Strong understanding of data preprocessing, feature engineering, and model evaluation. Good-to-Have Familiarity with ML pipelines, and orchestration tools. Experience with feature stores, vector databases, or event-driven ML systems. Knowledge of DevOps practices in cloud environments (Terraform, GitHub Actions, Jenkins, etc.). Cloud certifications. Exposure to monitoring, alerting, and observability tools (Prometheus, Grafana, ELK, etc.).

Preferred Skills (Bonus Points): Familiarity with multi-agent orchestration frameworks . Experience in human-in-the-loop AI , knowledge extraction , or clinical/pharma R&D . Knowledge of Responsible AI principles , red teaming , or AI risk assessment . Strong backend development experience with emphasis on code quality , logging , and automated testing . Exposure to semantic search , vector databases , or embedding optimization techniques . Why Join Us? Work at the cutting edge of GenAI, multi-agent systems, and enterprise automation . Build impactful AI solutions in domains such as healthcare , life sciences , R&D , and finance . Collaborate with world-class engineers, scientists, and innovators in a high-performance team. Opportunity to define and shape the next-gen AI platforms and infrastructure. About the Role: We are hiring an experienced AI/ML Engineer with strong expertise in Generative AI , LLMOps , and agentic AI systems . This role blends the cutting edge of multi-agent orchestration , LLM pipelines , and MLOps best practices . You will be responsible for designing and deploying autonomous agents powered by LLMs, optimizing GenAI pipelines, and ensuring responsible, secure, and scalable AI operations. Youll work across diverse domains including annotation automation, knowledge graph generation, drug discovery, clinical R&D, and enterprise data orchestration . Key Responsibilities: Design & Develop GenAI Agents: Build intelligent agents using frameworks like LangChain , AutoGen , LangGraph , or Semantic Kernel for tasks such as summarization, labeling, document classification, and data annotation. Orchestrate Multi-Agent Systems: Implement memory/state management, decision-making strategies, and inter-agent communication using LLMs and reinforcement learning. LLMOps & Pipeline Development: Develop end-to-end LLMOps pipelines for fine-tuning, deployment, monitoring, and evaluation of LLMs using MLflow , Azure , GCP , or AWS . Responsible AI & Governance: Enforce compliance with governance frameworks (GDPR, AI Act) and embed explainability, fairness, and transparency into AI systems. Security & Infrastructure: Integrate secure deployment practices, access controls, model sandboxing, and cloud-native CI/CD systems for scalable GenAI products. RAG & Vector Search: Build Retrieval-Augmented Generation (RAG) pipelines using FAISS , Pinecone , or similar tools, and optimize LLM context windows and embeddings. Model Lifecycle & Observability: Automate training, fine-tuning (PEFT, RLHF), rollback, and real-time monitoring for GenAI agents and models. Collaboration & Impact: Work closely with MLOps, DevSecOps, Data Scientists , and product teams to drive real-world GenAI applications in healthcare, pharma, finance, and enterprise data systems. Required Qualifications: Bachelor's or Master's degree in Computer Science, AI/ML, Engineering, or related fields. 36 years of experience in AI/ML Engineering with at least 12 years in GenAI/LLM-based systems . Strong hands-on experience with Python , PyTorch/TensorFlow , and LLM frameworks like LangChain , LlamaIndex , Hugging Face , or AutoGen . Proficiency in cloud platforms: Azure , GCP , or AWS and containerization tools like Docker . Sound understanding of prompt engineering , NLP , Reinforcement Learning , and model evaluation . Experience building or integrating agentic frameworks , LLM pipelines , and AI observability systems . Apply Now if You Have: A passion for building intelligent, autonomous AI systems Proven track record of deploying LLM-based applications at scale A drive to create real-world impact with GenAI

Project Role : Responsible AI Engineer Project Role Description : Assess AI systems for adherence to predefined thresholds and benchmarks related to responsible, ethical and sustainable practices. Design and implement technology mitigation strategies for systems to ensure ethical and responsible standards are achieved. Must have skills : Responsible AI Good to have skills : NA Minimum 12 year(s) of experience is required Educational Qualification : 15 years full time education Summary: As a Responsible AI Engineer, you will assess AI systems for adherence to predefined thresholds and benchmarks related to responsible, ethical, and sustainable practices. Design and implement technology mitigation strategies for systems to ensure ethical and responsible standards are achieved. Roles & Responsibilities: - Expected to be a SME with deep knowledge and experience. - Should have Influencing and Advisory skills. - Responsible for team decisions. - Engage with multiple teams and contribute on key decisions. - Expected to provide solutions to problems that apply across multiple teams. - Develop and implement responsible AI frameworks. - Conduct audits and assessments of AI systems for ethical compliance. - Collaborate with cross-functional teams to ensure responsible AI practices are integrated. Professional & Technical Skills: - Must To Have Skills: Proficiency in Responsible AI. - Strong understanding of statistical analysis and machine learning algorithms. - Experience with data visualization tools such as Tableau or Power BI. - Hands-on implementing various machine learning algorithms such as linear regression, logistic regression, decision trees, and clustering algorithms. - Solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity. Additional Information: - The candidate should have a minimum of 15 years of experience in Responsible AI. - A 15 years full-time education is required.