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Ai Alignment Jobs in Connecticut (NOW HIRING)

Lead the vendor platform relationship, including contract performance, escalation management, roadmap alignment, licensing, and ongoing commercial oversight. * Own the AI platform cost and license ...

Review and guide solution designs to ensure alignment with AI CoE standards and enterprise architecture . Mentor and guide developers on GenAI patterns, tools, and best practices Development ...

Align AI and data initiatives with business strategy and value realization * Establish standards for scalable, reusable AI and data capabilities * Serve as a trusted advisor to CIO and business ...

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Align AI and data initiatives with business strategy and value realization * Establish standards for scalable, reusable AI and data capabilities * Serve as a trusted advisor to CIO and business ...

VP, AI Enablement

Stamford, CT · On-site

$170 - $290/hr

Drive rollout of AI tools and priority use cases across the organization, ensuring launch readiness, stakeholder alignment, associate-facing guidance, adoption support, and post-launch learning loops.

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Accountable for portfolio-level AI governance ensuring alignment with Legal, Compliance, Model Risk, Privacy, Security, and Audit partners. Maintain readiness for audits and regulatory review by ...

AVP Applied AI

Hartford, CT · On-site +1

$182K - $273K/yr

Accountable for portfolio-level AI governance ensuring alignment with Legal, Compliance, Model Risk, Privacy, Security, and Audit partners. Maintain readiness for audits and regulatory review by ...

AI Solutions Architect

Norwalk, CT · On-site

$63.25 - $83.50/hr

Provide architecture oversight for multiple concurrent AI initiatives and ensure alignment with enterprise technology standards, security policies, and strategic roadmaps. * Evaluate and recommend AI ...

AI Solutions Architect

Norwalk, CT · On-site

$125K - $167K/yr

Provide architecture oversight for multiple concurrent AI initiatives and ensure alignment with enterprise technology standards, security policies, and strategic roadmaps. * Evaluate and recommend AI ...

AI Solutions Architect

Norwalk, CT · On-site

$126 - $168/hr

Provide architecture oversight for multiple concurrent AI initiatives and ensure alignment with enterprise technology standards, security policies, and strategic roadmaps. * Evaluate and recommend AI ...

... alignment with best practices Collaborate with architects and technical leads to identify and address potential risks and challenges in AI implementations Maintain documentation of architecture ...

AI Security Architect

Hartford, CT

$65.50 - $84.75/hr

Review and approve AI solution designs to ensure alignment with security, privacy, and resilience requirements * Design controls for secure data pipelines, secure model storage, controlled model ...

The AI Legal Engineer is responsible for partnering with subject matter experts to design, build ... Embed human-review checkpoints and audit mechanisms aligned with Firm governance, confidentiality ...

AI Architect

Winchester Center, CT · On-site

$61 - $80.25/hr

... aligned with enterprise standards. • Ensure solutions are scalable, resilient, secure, and cloud enabled. 2. Wealth Management Platform Integration • Architect integrations across: o CRM ...

Maintain alignment with relevant standards and regulations (as applicable) and ensure internal AI policies and procedures are current and auditable. * Third-party and vendor risk: Conduct due ...

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Ai Alignment information

What is AI alignment?

AI alignment refers to the process of ensuring that artificial intelligence systems act in ways that are aligned with human values, intentions, and ethical standards. This field focuses on designing AI models that not only achieve their objectives but also do so safely and beneficially for humanity. As AI systems become more advanced, alignment becomes increasingly important to prevent unintended consequences or harmful behaviors. Researchers in AI alignment work on technical solutions, such as value learning and interpretability, as well as broader ethical and policy considerations.

What are some common challenges faced by professionals working in AI alignment roles?

Professionals in AI alignment roles often encounter the challenge of translating complex ethical principles and human values into machine-understandable objectives. Balancing technical constraints with theoretical considerations requires close collaboration with cross-functional teams, including ethicists, engineers, and product managers. Additionally, the rapidly evolving landscape of artificial intelligence demands continuous learning to stay current with new alignment techniques and research findings. Navigating these challenges can be intellectually stimulating and offers significant opportunities for interdisciplinary growth.

What are the key skills and qualifications needed to thrive as an AI alignment specialist, and why are they important?

To thrive as an AI Alignment Specialist, you need a strong background in computer science, mathematics, and machine learning, often evidenced by an advanced degree in a related field. Familiarity with technical tools such as Python, TensorFlow, PyTorch, and formal verification systems is typically required, along with understanding of AI safety principles. Analytical thinking, ethical reasoning, and effective communication are crucial soft skills for success in this role. These skills ensure that AI systems are developed safely, ethically, and in alignment with human values, which is essential for mitigating risks associated with advanced AI.

What is the difference between Ai Alignment vs Data Scientist?

AspectAi AlignmentData Scientist
Required CredentialsAdvanced degrees in AI, Machine Learning, or related fieldsDegree in Data Science, Statistics, Computer Science, or related fields
Work EnvironmentResearch labs, AI development companies, tech firmsTech companies, finance, healthcare, consulting firms
Industry UsageFocuses on ensuring AI systems behave as intendedAnalyzes data to extract insights and build predictive models

While both roles involve advanced technical skills, Ai Alignment specialists focus on aligning AI systems with human values and safety, whereas Data Scientists analyze data to inform business decisions. The roles often overlap in AI research environments but serve different primary objectives.

What are popular job titles related to Ai Alignment jobs in Connecticut?

For Ai Alignment jobs in Connecticut, the most frequently searched job titles are:

What cities in Connecticut are hiring for Ai Alignment jobs?

Cities in Connecticut with the most Ai Alignment job openings:

Infographic showing various Ai Alignment job openings in Connecticut as of August 2026, with employment types broken down into 74% Full Time, 19% Part Time, 2% Temporary, and 5% Contract. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution.

Other

Posted 16 days ago


Job description

Title: AI Architect
Duration: 6 months
Location: Remote
Overview

The AI Architect is responsible for designing, developing, and governing enterprise-grade AI solutions that align with business strategy. This role blends deep technical expertise in artificial intelligence, machine learning, data, and cloud architecture with strong product intuition, security awareness, and leadership. The AI Architect ensures that AI initiatives are scalable, ethical, secure, cost-efficient, and integrated into the broader enterprise ecosystem.

Key Responsibilities<>AI Strategy & Solution Architecture
  • Define and evolve the enterprise AI architecture, ensuring alignment with business, data, and technology strategies.
  • Design scalable, secure, and compliant automation solutions to streamline across the enterprise.
  • Architect end-to-end AI solutions including data engineering, RAG model development, model operations (MLOps), and lifecycle management.
  • Partner with business, product, and engineering teams to translate business problems into appropriate AI/ML approaches.
  • Develop reference architectures and reusable patterns for generative AI, Agentic AI, predictive models, conversational systems, and intelligent automation.
<>Required Qualifications
  • Bachelor’s degree in Computer Science, Engineering, or a related technical field.
  • 5 years of experience in application development, engineering, or solution delivery roles.
  • 1 year of hands-on experience in AI/ML engineering, data science, or AI solution architecture.
  • Strong hands-on experience with machine learning frameworks and LLM platforms (e.g., OpenAI, Azure AI Foundry, Copilot Studio/Agent Builder, or comparable generative AI ecosystems).
  • Deep expertise in cloud platforms, particularly Microsoft Azure, and modern architectural patterns (microservices, event-driven architectures, API-first design).
  • Proficiency in one or more of the following: Python, Azure Machine Learning, or related AI/ML tooling.
  • Experience with MLOps/LLMOps ecosystems, including tools such as MLflow, Kubernetes, LangChain, vector databases, and feature stores.
  • Strong hands-on experience with ML frameworks, LLM platforms - OpenAI, MSFT/Azure Cloud Foundry, Copilot Studio Agent Builder, low code/no code platforms, and generative AI tools.
  • Background in RAG systems, model fine-tuning, embeddings, vector storage, and retrieval optimization.
<>Preferred Qualifications
  • Experience in enterprise-wide AI programs or platform buildouts.
  • Strong understanding of data governance, privacy, security, and model risk management.
  • Prior experience with large-scale transformation programs.
<>Technical Leadership
  • Provide architectural oversight across AI/ML projects to ensure consistency, performance, and maintainability.
  • Evaluate and select AI technologies, frameworks, cloud services, vector databases, LLM orchestration frameworks, and tooling.
  • Support development teams on model selection, training pipelines, prompt engineering, fine-tuning, RAG (Retrieval-Augmented Generation), and evaluation methodologies.
  • Mentor engineers, analysts, and product teams on AI best practices.
<>Data, Integration & Platforms
  • Partner with data architects and engineering to ensure robust data pipelines, governance, feature stores, and architecture.
  • Design secure and performant integration between AI models and enterprise systems (APIs, microservices, events).
<>Governance & Compliance
  • Ensure AI solutions adhere to enterprise security standards, data privacy policies, and regulatory requirements.
  • Implement responsible AI guardrails, fairness checks, explainability frameworks, and monitoring.
  • Develop and maintain automation governance frameworks, documentation, and audit trails.
<>Operations & Optimization
  • Define MLOps / LLMOps standards including CI/CD pipelines, model monitoring, drift detection, observability, and rollback processes.
  • Drive continuous improvement of model performance, cost optimization, and operational efficiency.
  • Establish KPIs, telemetry, and feedback loops for production AI systems.
<>Collaboration & Enablement
  • Partner with IT, compliance, operations, and customer service teams to align automation initiatives with business goals.
  • Mentor and guide developers and analysts to build a center of excellence (CoE) for automation.