ai technical lead

Pfizer

<div></div><div><div>ROLE SUMMARY</div><div></div><div>
The AI Acceleration (AIA) function within the Chief Marketing Office (CMO) is the single, business-led engine that owns the design, delivery, and scale-up of priority AI capabilities across Commercial. AIA works in tight collaboration with various Pfizer functions to deploy and maintain production-grade AI solutions that simplify how we work and drive measurable value across all processes.</div><div></div><div>
As a Technical Lead in the newly formed AIA team, we are looking for a hands-on solution architect to lead the design and implementation of end-to-end agentic AI solutions at enterprise scale. This role requires expertise across AI architecture, cloud engineering, data platforms, MLOps/LLOps and product thinking. The ideal candidate should be comfortable engaging directly with business stakeholders, translating ambiguous needs into technical solutions, developing MVPs and guiding engineering team toward scalable delivery.</div><div></div><div>
Role Responsibilities</div><div></div><div>
Solution Design &amp; Architecture</div><ul><li><div>
Architect enterprise-grade AI solutions integrating LLMs, RAG, autonomous agents, vector search, orchestration frameworks, APIs and UI layers</div></li></ul><ul><li><div>
Implements scalable E2E AI pipelines- data-&gt; semantic layer-&gt; embeddings-&gt; vector DB-&gt; inference-&gt; monitoring</div></li><li><div>
Own architecture documentation, solutions diagrams and technical decision logs</div></li><li><div>
Act as player coach-able to prototype agents, build POCs and guide engineering teams production systems</div></li></ul><div>
Cross-Functional Collaboration</div><ul><li><div>
Partner with Product Owners, Data Scientists, Engineers, and Business Stakeholders to translate requirements into technical solutions.</div></li></ul><ul><li><div>
Facilitate workshops and design sessions to gather insights and co-create technical solution blueprints.</div></li></ul><ul><li><div>
Ensure integration of AI solutions with existing enterprise systems and data environment. Push boundaries of technical innovation at the enterprise level.</div></li></ul><div>
Technical Leadership &amp; Governance</div><ul><li><div>
Define and enforce architectural standards, best practices, and design patterns for AI and digital health solutions.</div></li></ul><ul><li><div>
Set the standard for and lead technical reviews, risk assessments, and design validations.</div></li></ul><ul><li><div>
Ensure solutions adhere to data privacy, security, and regulatory requirements (e.g., HIPAA, GDPR, ANVISA, COFEPRIS).</div></li><li><div>
Ensure security, scalability, privacy safeguards, hallucination risk control and responsible AI implementation</div></li><li><div>
Establish guardrails for model usage, evaluation metrics, monitoring and fallback plans</div></li></ul><div>
Innovation &amp; Emerging Technologies</div><ul><li><div>
Stay abreast of emerging AI technologies, platforms, and trends relevant to healthcare and life sciences.</div></li></ul><ul><li><div>
Evaluate and prototype new tools (e.g., LLMs, federated learning, edge AI) for potential adoption.</div></li></ul><ul><li><div>
Drive innovation by identifying opportunities for AI to enhance patient outcomes, operational efficiency, and market differentiation.</div></li></ul><ul><li><div>
Documentation &amp; Knowledge Management</div></li></ul><ul><li><div>
Develop and maintain comprehensive architecture documentation, including diagrams, data flows, and technical specifications.</div></li></ul><ul><li><div>
Create reusable solution templates and reference architectures for future projects. Develop platform strategies to empower teams with consistent and re-usable patterns</div></li></ul><ul><li><div>
Contribute to internal knowledge bases and technical communities of practice.</div></li></ul><ul><li><div>
Vendor &amp; Partner Engagement</div></li></ul><ul><li><div>
Assess and manage relationships with external technology vendors, cloud providers, and implementation partners.</div></li></ul><ul><li><div>
Lead technical due diligence and integration planning for third-party AI solutions.</div></li></ul><ul><li><div>
Ensure vendor solutions align with internal architecture and compliance standards.</div></li></ul><div></div><div>
BASIC QUALIFICATIONS</div><ul><li><div>
Bachelor&rsquo;s degree in Computer Science, Engineering, data Science or related field.</div></li><li><div>
9+ years of relevant experience in AI/ML/Data/SaaS engineering roles with 2+ years in architecture capacity</div></li><li><div>
Proven experience in designing and deploying AI solutions in healthcare or regulated industries.</div></li><li><div>
Deep understanding of cloud platforms (e.g., Azure, AWS, GCP), microservices, APIs, and data engineering.</div></li><li><div>
Familiarity with AI/ML frameworks (e.g., TensorFlow, PyTorch), MLOps, and model lifecycle management.</div></li><li><div>
Hands-on experience with</div></li></ul><ul><li><div>
Data Tech: Snowflake/Kafka/Spark</div></li><li><div>
APIs &amp; Microservices: Python, FastAPI, REST</div></li><li><div>
MLOps/LLMOps: MLflow, Vertex AI</div></li><li><div>
LLMs, RAG, LangGraph/OpenAI</div></li></ul><ul><li><div>
Excellent communication, stakeholder management, and analytical skills.</div></li><li><div>
Strong knowledge of agile methodologies and DevOps practices.</div></li></ul><div>
Preferred Qualifications:</div><ul><li><div>
Master&rsquo;s degree or PhD in Computer Science, Data Science, or related field.</div></li><li><div>
Experience in pharmaceutical or healthcare technology environments.</div></li><li><div>
Experience with Agentic AI frameworks (CrewAI, AutoGen, Hugging Face agents, OpenAI workflows)</div></li><li><div>
Familiarity with compliance standards such as GxP, HIPAA, and data privacy regulations.</div></li><li><div>
Knowledge of enterprise workflow tools &ndash; Salesforce, ServiceNow, SAP, Veeva etc</div></li><li><div>
Demonstrated success in deploying AI or ML solutions in production environments.</div></li></ul><div></div><div>
Pfizer is an equal opportunity employer and complies with all applicable equal employment opportunity legislation in each jurisdiction in which it operates.</div><div></div>
Information &amp; Business Tech</div><div></div>

Senior Manager, Technical Lead

Artificial Intelligence Global Company

<div>
 <p>
  Artificail Intelegence Global Company is seeking a highly experienced and technically grounded
  <strong>
   AI Lead
  </strong>
  to lead and support client engagements in the
  <strong>
   government, PIF and public sector
  </strong>
  . This role blends
  <strong>
   technical expertise in AI
  </strong>
  with
  <strong>
   consulting acumen and business development capabilities
  </strong>
  , driving strategic initiatives, identifying opportunities, and delivering value-driven solutions to government, PIF and public entities.
 </p>
 <p>
  The ideal candidate will have
  <strong>
   7+ years of experience
  </strong>
  with a solid background in
  <strong>
   AI, machine learning, and data platforms
  </strong>
  , while also being skilled at
  <strong>
   stakeholder engagement, pre-sales, proposal development
  </strong>
  , and
  <strong>
   client delivery
  </strong>
  . This role is pivotal in bridging technical possibilities with public sector needs to ensure effective transformation and value realization.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Roles &amp; Responsibilities :
  </strong>
 </p>
 <ul>
  <li>
   <strong>
    Client Engagement &amp; Consulting:
   </strong>
  </li>
  <li>
   Lead AI and data advisory engagements with public sector clients, understanding their mission objectives and aligning solutions accordingly.
  </li>
  <li>
   Serve as a trusted advisor to senior government stakeholders, presenting technical concepts in business terms.
  </li>
  <li>
   Conduct AI/ML and data maturity assessments, feasibility studies, and roadmap development.
  </li>
  <li>
   <strong>
    Business Development:
   </strong>
  </li>
  <li>
   Support proposal writing and RFI/RFP responses for government tenders.
  </li>
  <li>
   Identify and cultivate opportunities for AI and data engagements within provincial and central government, PIF &amp; public sectors.
  </li>
  <li>
   Collaborate with sales teams and technical teams to tailor solutions that meet client needs and procurement requirements.
  </li>
  <li>
   <strong>
    Solution Architecture &amp; Delivery Oversight:
   </strong>
  </li>
  <li>
   Oversee design and implementation of AI/ML and data solutions tailored for public sector contexts (e.g., compliance, privacy, scalability).
  </li>
  <li>
   Guide data science and engineering teams in creating actionable models and platforms.
  </li>
  <li>
   Leadership &amp; Innovation:
  </li>
  <li>
   Stay abreast of emerging AI technologies, regulatory changes, and government policy trends.
  </li>
  <li>
   Contribute to Proof of Concepts (PoCs) and strategic AI frameworks for public sector transformation.
  </li>
 </ul>
 <p>
  <strong>
   <u>
    Education and Qualifications
   </u>
  </strong>
 </p>
 <ul>
  <li>
   Bachelor&rsquo;s degree in
   <strong>
    Computer Science, Data Science, Engineering, or related field
   </strong>
   . Master&rsquo;s degree preferred.
  </li>
  <li>
   Certifications in cloud platforms (e.g., AWS, Azure, GCP, Huawei, Oracle), AI/ML tools, and project management (e.g., PMP).
  </li>
  <li>
   Familiarity with
   <strong>
    government procurement
   </strong>
   and
   <strong>
    compliance frameworks like SDAIA regulations and NDMO.
   </strong>
  </li>
 </ul>
 <p>
  <strong>
   <u>
    Experience
   </u>
  </strong>
 </p>
 <ul>
  <li>
   <strong>
    12+ years
   </strong>
   of experience in technology consulting and deployment projects, with a focus on
   <strong>
    AI, ML, and data,
   </strong>
   including Advanced Analytics, Business Intelligence (BI), Computer Vision, Natural Language Processing (NLP), Generative AI (GenAI), AI Agents, and other emerging AI technologies
  </li>
  <li>
   Minimum
   <strong>
    5 years
   </strong>
   of client-facing experience in a
   <strong>
    consulting or business development
   </strong>
   capacity.
  </li>
  <li>
   Proven track record of engaging with
   <strong>
    government, PIF, and public sector
   </strong>
   clients.
  </li>
  <li>
   Experience in
   <strong>
    developing proposals
   </strong>
   ,
   <strong>
    responding to RFPs/RFIs
   </strong>
   , and
   <strong>
    managing technical presales cycles
   </strong>
   .
  </li>
  <li>
   Background in delivering or overseeing the delivery of
   <strong>
    AI/ML use cases and projects
   </strong>
   , data analytics platforms, and data governance frameworks.
  </li>
 </ul>
 <p>
  <strong>
   <u>
    Competency
   </u>
  </strong>
 </p>
 <ul>
  <li>
   Strong grasp of
   <strong>
    AI/ML algorithms
   </strong>
   ,
   <strong>
    data engineering
   </strong>
   ,
   <strong>
    data architecture
   </strong>
   , and
   <strong>
    MLOps
   </strong>
   .
  </li>
  <li>
   Familiarity with AI technologies and tools (e.g., TensorFlow, PyTorch, scikit-learn, Databricks).
  </li>
  <li>
   Knowledge of
   <strong>
    cloud data platforms
   </strong>
   (e.g., Azure Synapse, AWS Sagemaker, GCP BigQuery).
  </li>
  <li>
   <strong>
    Consulting &amp; Business Development:
   </strong>
   Strong experience in
   <strong>
    client engagement, requirements gathering, solution scoping
   </strong>
   , and
   <strong>
    executive communication
   </strong>
   .
  </li>
  <li>
   Ability to create
   <strong>
    winning proposals
   </strong>
   , present
   <strong>
    value propositions
   </strong>
   , and conduct
   <strong>
    strategic account planning
   </strong>
   .
  </li>
  <li>
   Strategic thinker with a consultative mindset and problem-solving orientation.
  </li>
  <li>
   <strong>
    Sector-Specific Knowledge:
   </strong>
   Understanding of public sector challenges such as
   <strong>
    data privacy, ethics, digital inclusion
   </strong>
   , and
   <strong>
    legacy modernization
   </strong>
   .
  </li>
  <li>
   Familiarity with
   <strong>
    policy-driven AI development
   </strong>
   ,
   <strong>
    regulatory compliance
   </strong>
   , and
   <strong>
    governance frameworks
   </strong>
   .
  </li>
  <li>
   <strong>
    Excellent communication and interpersonal skills
   </strong>
   &ndash; able to influence both technical and non-technical stakeholders.
  </li>
  <li>
   <strong>
    Leadership and mentoring skills
   </strong>
   &ndash; able to guide teams and junior consultants.
  </li>
  <li>
   Strong
   <strong>
    organizational, analytical
   </strong>
   , and
   <strong>
    presentation abilities
   </strong>
   .
  </li>
  <li>
   Willingness to
   <strong>
    travel
   </strong>
   as needed to client sites.
  </li>
 </ul>
 <p>
 </p>
</div>


Artificial Intelligence Practice Lead

Infogain

<p></p><div><p>ROLES &amp; RESPONSIBILITIES</p>
<div><p><b>Core Skills</b></p><p>
Expertise in developing and optimizing complex AI/ML applications Strong understanding of AI/ML libraries and frameworks like TensorFlow, Keras, PyTorch, etc. Experience in using AI/ML development tools and technologies Familiarity with software testing and debugging best practices.</p><p>
Core Skills Expertise in developing and optimizing complex AI/ML applications Strong understanding of AI/ML libraries and frameworks like TensorFlow, Keras, PyTorch, etc. Experience in using AI/ML development tools and technologies Familiarity with software testing and debugging best practices.Core SkillsKey Responsibilities ? Solution Architecture &amp;amp; Development o Lead the end-to-end development of GenAI solutions, from ideation to production deployment. o Architect and implement scalable GenAI applications using frameworks like LangChain, LangGraph, AutoGen, CrewAI, or equivalent. o Integrate LLMs (OpenAI GPT, Claude, Mistral, LLaMA, etc.) with enterprise data sources and APIs to enable advanced RAG (Retrieval-Augmented Generation), multi-agent workflows, and context-aware conversational AI. ? Technical Leadership o Mentor and guide a team of AI engineers and developers, fostering a culture of innovation and technical excellence. o Define coding standards, best practices, and DevOps/MLOps pipelines for model training, fine-tuning, and deployment. o Collaborate with data scientists to optimize models for performance, cost, and accuracy. ? Stakeholder Collaboration o Partner with product managers, business leaders, and domain experts to identify high-value GenAI use cases. o Present technical roadmaps, proof-of-concepts, and solution demos to senior leadership and clients. ? Governance &amp;amp; Security o Implement robust data governance, privacy, and compliance controls (e.g., PII masking, GDPR) for AI-driven applications. o Ensure adherence to ethical AI principles and responsible use of Generative AI technologies. Required Skills &amp;amp; Experience ? Technical Expertise o 10+ years of overall IT/Software development experience, with at least 3+ years focused on Generative AI, LLMs, or advanced AI/ML. o Proficiency in Python, Node.js, or equivalent languages for AI solution development. o Hands-on experience with vector databases (Pinecone, Weaviate, FAISS), embedding models, and RAG pipelines. o Familiarity with cloud platforms (Azure OpenAI, AWS Bedrock, GCP Vertex AI) and containerized deployments (Docker, Kubernetes). o Strong understanding of prompt engineering, fine-tuning, and multi-agent orchestration. ? Leadership &amp;amp; Delivery o Proven track record of leading cross-functional development teams to deliver enterprise-scale AI products. o Experience with Agile/Scrum methodologies and project management tools (Jira, Azure DevOps). ? Domain Knowledge o Exposure to industries like retail, finance, healthcare, or QSR (preferred). o Understanding of data governance, security, and compliance in AI/ML applications. Preferred Qualifications ? Experience integrating GenAI with Power Platform (Power Automate, Copilot Studio) or enterprise SaaS ecosystems. ? Knowledge of MLOps and AI model monitoring frameworks. ? Certifications in AI/ML, Azure AI Engineer, or OpenAI/LangChain (a plus). ? Contributions to open-source AI projects or AI research publications. Key Attributes ? Strategic thinker with strong problem-solving and analytical skills. ? Excellent communication skills to engage both technical and non-technical stakeholders. ? Passion for emerging AI trends and the ability to rapidly learn new technologies.</p></div><br>
<p></p>
<p>EXPERIENCE</p>
<ul><div>3-4.5 Years</div>
</ul><p>SKILLS</p>
<ul><div>Primary Skill: AI/ML Development</div>
<div>Sub Skill(s): AI/ML Development
</div><div>Additional Skill(s): TensorFlow</div></ul></div><p></p>

AI / ML Developer (Standard)

Oracle

<div><p>At Oracle Health, we are redefining healthcare intelligence through cutting-edge AI and Search technologies. As a <b>Principal Machine Learning Engineer </b>, you will be responsible for designing and operationalizing scalable ML and LLM-powered systems that enhance clinical insights, streamline operations, and power intelligent search experiences across our products.
</p><p>You will serve as a <b>technical leader </b>, mentoring engineers and data scientists, defining solution architectures, and ensuring end-to-end reliability and performance in ML and Search pipelines.</p></div>
<br><div><p><b>Design and implement scalable AI and LLM applications </b>including RAG (Retrieval-Augmented Generation), embeddings, and multi-agent architectures for healthcare data and knowledge systems.
</p><p><b>Architect and optimize enterprise Search solutions </b>using <b>OpenSearch </b>(or Elasticsearch), including:
</p><p>Designing and maintaining <b>Universal Search Documents (USDs) </b>with rich metadata, relevance signals, and domain-specific ranking.
</p><p>Implementing efficient <b>indexing pipelines </b>and query optimization strategies for structured and unstructured healthcare data.
</p><p>Tuning search relevance using clickstream and behavioral <b>signals </b>, boosting, and custom scoring.
</p><p>Building <b>semantic search </b>layers using vector embeddings and hybrid retrieval (BM25 + ANN).
</p><p>Collaborate with data, engineering, and product teams to <b>integrate Search and ML pipelines </b>seamlessly into production.
</p><p>Establish and maintain <b>search performance monitoring </b>, relevance evaluation, and A/B experimentation frameworks.
</p><p>Lead teams in developing <b>responsible, explainable, and secure AI solutions </b>that comply with healthcare data standards and regulations.
</p><p>Mentor engineers and scientists, fostering technical excellence and innovation.
</p><p>Contribute to architecture reviews, patents, and thought leadership in AI and Search innovation.<br>
</p><p></p><b>Required Qualifications
</b><p>Master&rsquo;s or PhD in Computer Science, Data Science, or related technical field.
</p><p>8+ years of experience in ML or AI engineering, with at least <b>2 years of hands-on experience in OpenSearch (or Elasticsearch) </b>.
</p><p>Proven track record delivering <b>end-to-end AI or search-based applications </b>in production.
</p><p>Strong proficiency in <b>Python </b>, <b>PyTorch/TensorFlow </b>, and cloud platforms ( <b>OCI, AWS, or Azure </b>).
</p><p>Deep understanding of <b>LLMs </b>, <b>RAG pipelines </b>, and <b>embedding-based search </b>.
</p><p>Experience creating, maintaining, and optimizing <b>Universal Search Documents (USDs) </b>&mdash;including schema design, signals integration, and ranking models.
</p><p>Strong command of <b>query DSL </b>, aggregation frameworks, and <b>performance optimization </b>for OpenSearch clusters (e.g., sharding, caching, and scaling strategies).<br>
</p><p></p><b>Preferred Qualifications
</b><p>Experience integrating <b>LLMs with OpenSearch </b>for semantic and generative retrieval.
</p><p>Familiarity with <b>vector databases </b>, <b>hybrid retrieval systems </b>, or <b>cross-modal search </b>.
</p><p>Experience with <b>data pipeline orchestration </b>(Airflow, Prefect, or similar).
</p><p>Experience leading cross-functional AI/ML programs or search relevance initiatives.
</p><p>Knowledge of healthcare data systems, interoperability, and compliance frameworks (e.g., HIPAA, FHIR).
</p><p>Contributions to open-source search or ML communities, or published research in AI/ML.</p></div>

Software Developer

<p></p><div><p>ROLES &amp; RESPONSIBILITIES</p>
<div><p><b>Core Skills</b></p><p>
Strong leadership and communication skills to lead teams of AI/ML developers Experience in defining and implementing software development processes and best practices Expertise in advanced AI/ML concepts and tools like natural language processing, computer vision, TensorFlow, Keras, PyTorch, etc. Experience in integrating AI/ML with backend technologies like databases, messaging systems, etc. Strong understanding of software engineering principles and practices.</p><p>
Core Skills Expertise in developing and optimizing complex AI/ML applications Strong understanding of AI/ML libraries and frameworks like TensorFlow, Keras, PyTorch, etc. Experience in using AI/ML development tools and technologies Familiarity with software testing and debugging best practices.Core SkillsKey Responsibilities ? Solution Architecture &amp;amp; Development o Lead the end-to-end development of GenAI solutions, from ideation to production deployment. o Architect and implement scalable GenAI applications using frameworks like LangChain, LangGraph, AutoGen, CrewAI, or equivalent. o Integrate LLMs (OpenAI GPT, Claude, Mistral, LLaMA, etc.) with enterprise data sources and APIs to enable advanced RAG (Retrieval-Augmented Generation), multi-agent workflows, and context-aware conversational AI. ? Technical Leadership o Mentor and guide a team of AI engineers and developers, fostering a culture of innovation and technical excellence. o Define coding standards, best practices, and DevOps/MLOps pipelines for model training, fine-tuning, and deployment. o Collaborate with data scientists to optimize models for performance, cost, and accuracy. ? Stakeholder Collaboration o Partner with product managers, business leaders, and domain experts to identify high-value GenAI use cases. o Present technical roadmaps, proof-of-concepts, and solution demos to senior leadership and clients. ? Governance &amp;amp; Security o Implement robust data governance, privacy, and compliance controls (e.g., PII masking, GDPR) for AI-driven applications. o Ensure adherence to ethical AI principles and responsible use of Generative AI technologies. Required Skills &amp;amp; Experience ? Technical Expertise o 10+ years of overall IT/Software development experience, with at least 3+ years focused on Generative AI, LLMs, or advanced AI/ML. o Proficiency in Python, Node.js, or equivalent languages for AI solution development. o Hands-on experience with vector databases (Pinecone, Weaviate, FAISS), embedding models, and RAG pipelines. o Familiarity with cloud platforms (Azure OpenAI, AWS Bedrock, GCP Vertex AI) and containerized deployments (Docker, Kubernetes). o Strong understanding of prompt engineering, fine-tuning, and multi-agent orchestration. ? Leadership &amp;amp; Delivery o Proven track record of leading cross-functional development teams to deliver enterprise-scale AI products. o Experience with Agile/Scrum methodologies and project management tools (Jira, Azure DevOps). ? Domain Knowledge o Exposure to industries like retail, finance, healthcare, or QSR (preferred). o Understanding of data governance, security, and compliance in AI/ML applications. Preferred Qualifications ? Experience integrating GenAI with Power Platform (Power Automate, Copilot Studio) or enterprise SaaS ecosystems. ? Knowledge of MLOps and AI model monitoring frameworks. ? Certifications in AI/ML, Azure AI Engineer, or OpenAI/LangChain (a plus). ? Contributions to open-source AI projects or AI research publications. Key Attributes ? Strategic thinker with strong problem-solving and analytical skills. ? Excellent communication skills to engage both technical and non-technical stakeholders. ? Passion for emerging AI trends and the ability to rapidly learn new technologies.</p></div><br>
<p></p>
<p>EXPERIENCE</p>
<ul><div>8-11 Years</div>
</ul><p>SKILLS</p>
<ul><div>Primary Skill: AI/ML Development</div>
<div>Sub Skill(s): AI/ML Development
</div><div>Additional Skill(s): TensorFlow</div>
</ul><p>ABOUT THE COMPANY</p>
<p>Infogain is a human-centered digital platform and software engineering company based out of Silicon Valley. We engineer business outcomes for Fortune 500 companies and digital natives in the technology, healthcare, insurance, travel, telecom, and retail &amp; CPG industries using technologies such as cloud, microservices, automation, IoT, and artificial intelligence. We accelerate experience-led transformation in the delivery of digital platforms. Infogain is also a Microsoft (NASDAQ: MSFT) Gold Partner and Azure Expert Managed Services Provider (MSP).</p>
<p>
Infogain, an Apax Funds portfolio company, has offices in California, Washington, Texas, the UK, the UAE, and Singapore, with delivery centers in Seattle, Houston, Austin, Krak&oacute;w, Noida, Gurgaon, Mumbai, Pune, and Bengaluru.</p></div>

AI / ML Developer (Lead)

<p></p><div><p>ROLES &amp; RESPONSIBILITIES</p>
<div><p><b>Core Skills</b></p><p>
Strong understanding of AI/ML development concepts and syntax Experience in developing and debugging AI/ML applications Familiarity with version control systems like Git Knowledge of networking and operating system concepts</p><p>
Core SkillsStrong experience in developing and optimizing large-scale, complex AI/ML applications Expertise in advanced AI/ML concepts like natural language processing, computer vision, etc. Experience in performance optimization and scalability of AI/ML applications Familiarity with serverless architecture and cloud-based development Experience in leading teams of AI/ML developers and providing technical guidance.Core SkillsKey Responsibilities ? Solution Architecture &amp;amp; Development o Lead the end-to-end development of GenAI solutions, from ideation to production deployment. o Architect and implement scalable GenAI applications using frameworks like LangChain, LangGraph, AutoGen, CrewAI, or equivalent. o Integrate LLMs (OpenAI GPT, Claude, Mistral, LLaMA, etc.) with enterprise data sources and APIs to enable advanced RAG (Retrieval-Augmented Generation), multi-agent workflows, and context-aware conversational AI. ? Technical Leadership o Mentor and guide a team of AI engineers and developers, fostering a culture of innovation and technical excellence. o Define coding standards, best practices, and DevOps/MLOps pipelines for model training, fine-tuning, and deployment. o Collaborate with data scientists to optimize models for performance, cost, and accuracy. ? Stakeholder Collaboration o Partner with product managers, business leaders, and domain experts to identify high-value GenAI use cases. o Present technical roadmaps, proof-of-concepts, and solution demos to senior leadership and clients. ? Governance &amp;amp; Security o Implement robust data governance, privacy, and compliance controls (e.g., PII masking, GDPR) for AI-driven applications. o Ensure adherence to ethical AI principles and responsible use of Generative AI technologies. Required Skills &amp;amp; Experience ? Technical Expertise o 10+ years of overall IT/Software development experience, with at least 3+ years focused on Generative AI, LLMs, or advanced AI/ML. o Proficiency in Python, Node.js, or equivalent languages for AI solution development. o Hands-on experience with vector databases (Pinecone, Weaviate, FAISS), embedding models, and RAG pipelines. o Familiarity with cloud platforms (Azure OpenAI, AWS Bedrock, GCP Vertex AI) and containerized deployments (Docker, Kubernetes). o Strong understanding of prompt engineering, fine-tuning, and multi-agent orchestration. ? Leadership &amp;amp; Delivery o Proven track record of leading cross-functional development teams to deliver enterprise-scale AI products. o Experience with Agile/Scrum methodologies and project management tools (Jira, Azure DevOps). ? Domain Knowledge o Exposure to industries like retail, finance, healthcare, or QSR (preferred). o Understanding of data governance, security, and compliance in AI/ML applications. Preferred Qualifications ? Experience integrating GenAI with Power Platform (Power Automate, Copilot Studio) or enterprise SaaS ecosystems. ? Knowledge of MLOps and AI model monitoring frameworks. ? Certifications in AI/ML, Azure AI Engineer, or OpenAI/LangChain (a plus). ? Contributions to open-source AI projects or AI research publications. Key Attributes ? Strategic thinker with strong problem-solving and analytical skills. ? Excellent communication skills to engage both technical and non-technical stakeholders. ? Passion for emerging AI trends and the ability to rapidly learn new technologies.</p></div>
<p>EXPERIENCE</p>
<ul><div>2-3 Years</div>
</ul><p>SKILLS</p>
<ul><div>Primary Skill: AI/ML Development</div>
<div>Sub Skill(s): AI/ML Development
</div><div>Additional Skill(s): TensorFlow</div></ul></div><p></p>

AI / ML Developer (Associate)

Devsinc

<div>
 Devsinc is seeking a highly experienced
 <strong>
  Senior AI Engineer
 </strong>
 with
 <strong>
  3+ years of professional AI/ML experience
 </strong>
 to design, build, and deploy advanced AI systems in production environments. The ideal candidate brings strong software engineering fundamentals, deep expertise in machine learning and large language models (LLMs), and proven experience delivering scalable, real-world AI solutions. This role demands architectural ownership, technical leadership, and the ability to guide cross-functional teams through complex, end-to-end AI initiatives, from concept to deployment
 <strong>
  .
  <br/>
  <br/>
 </strong>
 <strong>
  Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Lead end-to-end development and delivery of AI initiatives, from concept to production deployment.
  </li>
  <li>
   Design, develop, and optimize AI/ML models including deep learning, NLP, computer vision, LLMs, and embedding-based systems.
  </li>
  <li>
   Build scalable pipelines for training, fine-tuning, evaluation, deployment, and continuous optimization.
  </li>
  <li>
   Develop production-ready inference services, APIs, and microservices with a strong focus on performance, reliability, and cost efficiency.
  </li>
  <li>
   Implement and manage MLOps workflows using tools such as SageMaker, MLflow, Vertex AI, W&amp;B, Docker, and Kubernetes.
  </li>
  <li>
   Apply advanced model optimization techniques including quantization, distillation, batching, and GPU/TPU acceleration.
  </li>
  <li>
   Conduct experiments, research emerging AI techniques (LLMs, RAG, multimodal AI, vector search), and apply findings to real-world use cases.
  </li>
  <li>
   Collaborate with Data Engineering, Product, DevOps, and Business teams to deliver AI-driven features.
  </li>
  <li>
   Mentor junior and mid-level engineers, promoting best practices in AI and software engineering.
  </li>
  <li>
   Participate in system architecture design, CI/CD implementation, monitoring, and lifecycle management of AI systems.
  </li>
  <li>
   Ensure high standards of code quality, documentation, security, and compliance throughout the AI development lifecycle
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Requirements
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Bachelor's degree in Computer Science, Artificial Intelligence, Software Engineering, or a related field
  </li>
  <li>
   3+ years of professional experience in AI/ML engineering roles, with Strong communication, collaboration, and leadership skills
  </li>
  <li>
   Strong proficiency in Python and hands-on experience with PyTorch and/or TensorFlow.
  </li>
  <li>
   Proven experience deploying AI models in production at scale (APIs, microservices, real-time pipelines).
  </li>
  <li>
   Solid understanding of ML algorithms, feature engineering, dataset preparation, model evaluation, and optimization.
  </li>
  <li>
   Hands-on Experience with cloud platforms (AWS/GCP) and container orchestration (Kubernetes)
  </li>
  <li>
   Experience with distributed systems, GPU acceleration, and parallel computing.
  </li>
  <li>
   Hands-on experience with LLMs, RAG pipelines, vector databases, fine-tuning techniques (LoRA, QLoRA, PEFT), and building AI agents, workflow orchestration systems, or multimodal AI solutions.
  </li>
  <li>
   Strong understanding of data engineering concepts, real-time/streaming architectures, Kafka, Spark, ML infrastructure, along with model security, responsible AI, compliance, and risk mitigation
  </li>
  <li>
   Proficiency with version control systems and CI/CD pipelines
  </li>
  <li>
   Collaborative - works effectively with cross-functional teams.
  </li>
  <li>
   Team Player - mentors peers and contributes to collective success.
  </li>
  <li>
   Leadership-Oriented - capable of guiding teams and owning technical direction.
  </li>
  <li>
   Growth Minded - eager to learn and adapt to emerging AI technologies.
  </li>
  <li>
   Adaptable - thrives in fast-paced, dynamic environments.
  </li>
  <li>
   Customer-Centric - focused on building AI solutions that deliver real business value
  </li>
 </ul>
</div>


Senior Software Engineer - Artificial Intelligence

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