Softblues

About the Role:

We are looking for a visionary Marketing Operations Manager to lead our transition into an AI-first content organization. You will operate at the critical intersection of Content Strategy, Agentic AI Engineering, and Marketing Automation, building the "brain" behind our brand’s digital presence.

Your role includes, but is not limited to:

• Design and deploy sophisticated agentic workflows using AI-frameworks to automate complex content tasks;
• Build and maintain autonomous agents that monitor LinkedIn and X for intent signals to perform real-time engagement and brand-aligned outreach, while orchestrating workflows that enrich lead data from Crunchbase, ZoomInfo, etc. to drive hyper-personalized communication;
• Ensure seamless data flow between AI agents and the GTM stack by integrating intelligent triggers into Apollo, HubSpot, and Instantly.ai, ensuring every automated action is rooted in up-to-date context and deep target audience analysis;
• Develop intelligent agents that track industry shifts and competitor activity across web and social sources, automatically feeding these updates back into the content strategy and outreach logic to ensure our messaging remains relevant and adaptive to market changes in real-time;
• Implement "human-in-the-loop" architectures through intuitive interfaces (such as Slack), enabling the team to rapidly review and approve AI-generated content before publication or outreach, maintaining premium quality and an authentic brand voice;
• Manage the end-to-end flow of content, ensuring seamless integration between AI agents, LLMs, and marketing platforms;
• Define the "What, When, and Where" of our content engine, translating business goals into technical automation logic;
• Implement tracking and feedback loops to continuously tune agent prompts and model performance based on real-world engagement;
• Evaluate and integrate cutting-edge tools for SEO, scheduling, visual generation, and analytics.

What we’re looking for:

• Proven experience with LLMs (OpenAI, Claude, Gemini) and prompt engineering;
• Experience using AI / OpenAI API for lead enrichment or personalization;
• Deep understanding of content marketing, SEO, and brand positioning;
• Hands-on experience with GTM tools: Apollo, HubSpot/Salesforce, Instantly.ai, LinkedIn automation tools;
• Experience with tools like Make.com, n8n, or Zapier and a passion for "manual-zero" workflows;
• Ability to maintain and scale automation systems in production

Ready to shape the future of AI?

SoftBlues is looking for a highly capable and hands-on Project & Delivery Manager with a strong technical mindset and a proven track record in managing complex software lifecycles. In this role, you will be the driving force behind the delivery of our AI-powered products, ensuring seamless execution, high-quality standards, and the successful transformation of client visions into production-ready reality.

Responsibilities

• Define and maintain the product vision, roadmap, and feature backlog 
• Translate business goals, partner needs, and regulatory requirements into clear user stories, acceptance criteria, and technical specifications
• Prioritize backlog items based on value, risk, and strategic alignment
• Lead the end‑to‑end delivery lifecycle, ensuring predictable, high‑quality releases
• Facilitate agile ceremonies and remove delivery blockers
• Coordinate cross‑functional dependencies across engineering, QA, DevOps, compliance, and external teams
• Conduct tech estimations 
• Monitor delivery KPIs, team velocity, and release performance, driving continuous improvement
• Ensure delivery timelines are met while maintaining platform stability, scalability, and security
• Manage communication with internal stakeholders and external partners regarding delivery status, risks, and milestones
• Control budget and do regular reporting

Qualifications

• Have at least 3 years of proven experience in IT outsource companies as a Project Manager, Technical Product Manager, Delivery Manager, or similar hybrid role
• Experience managing multiple projects or parallel streams
• Experience using AI tools for prototyping products
• Bring a solid technical background with ability to engage in architectural discussions
• Have hands‑on experience working with agile software development teams
• Demonstrate excellent communication, stakeholder management, and prioritization skills
• Balance strategic thinking with tactical execution
• Ability to manage risks and resolve conflicts

Optimize Artifactory Setup to be scalable
We are modernizing JFrog Artifactory to simplify day to day use while preparing the platform for future scaling.
We are seeking an experienced Artifactory expert with proven expertise in enterprise-scale operation of artifact management platforms.

Tasks:
Conduct a comprehensive review of our existing Artifactory platform, develop optimization concepts, and implement enterprise-grade improvements including:

• Platform Assessment & Optimization: Analyze current setup, identify bottlenecks, and implement performance and security enhancements
• Cleanup Policies: Design and implement automated lifecycle management strategies for TB-scale artifact retention
• SCIM Integration: Architect and deploy enterprise-wide identity management and user provisioning
• Repository Restructuring: Plan and execute large-scale migration of repositories into optimized project structures
• Permission Management at Scale: Redesign and implement RBAC frameworks for complex, multi-tenant environments
• Continuous Improvement: Establish monitoring, governance, and alignment with industry best practices

Skills:

• Artifactory Deep Expertise:
• Multi-year production experience with JFrog Artifactory in complex enterprise environments
• Edge Nodes: Deep understanding of architecture, replication, and performance tuning
• Permission & User Management: Expert in complex RBAC structures and SCIM integration
• SCIM: Hands-on experience with SCIM-based user provisioning and identity management
• Project Organisation: Solid knowledge in enterprise-wide repository structuring and governance
• Repository Migration: Hands-on experience with large-scale migration projects (Repos to Projects)
• Cleanup Policies: Expertise in lifecycle management and storage optimization for TB-scale artifacts 
• API Mastery: Confident use of REST/GraphQL APIs for automation and integration
• Best Practices: Proven experience implementing Artifactory best practices
• Platform & Infrastructure Expertise:
  Kubernetes HA: Expert in operating highly available Artifactory clusters on Kubernetes
• OpenTofu: Solid knowledge in Infrastructure-as-Code for complex deployments
• Helm: Advanced knowledge in chart development and customization
• Production Operations: Experience with monitoring, incident response, and performance tuning
• Technical Documentation: Professional documentation of complex architectures (Markdown)
   

Nice to have:
ArgoCD: Hands-on experience with GitOps workflows

Business

Digital marketing agency that specializes in enhancing the digital presence and growth of automotive dealerships nationwide. Initially, they focused on supporting their service teams through automation tools and have since expanded to develop and sell white-label, productized services to their partners. Their mission is to deliver high-quality tools that meet the needs of their partners, leveraging their expertise in digital marketing to drive significant improvements and efficiencies in the automotive sector. The agency places a strong emphasis on building scalable, functional tools and fostering team growth through continuous improvement and collaboration.
 

Requirements

Client seeking a skilled Data Engineer with experience in architecting scalable data solutions using Amazon Web Services (AWS). This role will focus on building and maintaining data infrastructure to support our customer-facing tools, ensuring data is efficiently stored, processed, and available for analytics.

Overlap with EST is required
 

Key Responsibilities:

• Data Architecture Design: Architect, develop, and maintain scalable and robust data architectures using AWS services such as Amazon S3, RDS, Redshift, and EMR.
• ETL Processes: Design and implement ETL processes using AWS Glue, ensuring data is clean, reliable, and available for analysis.
• Data Pipeline Management: Develop and manage data pipelines using tools like Amazon Kinesis and AWS Lambda for real-time and batch processing.
• Database Management: Optimize databases using Amazon RDS and Redshift, ensuring data integrity, security, and performance.
• Data Lake Management: Utilize Amazon S3 for building and managing data lakes to store structured and unstructured data.
• Collaboration: Work closely with software engineers, data scientists, and product managers to ensure data solutions meet business requirements.
• Security and Compliance: Implement security best practices and ensure compliance with industry standards and regulations.
• Monitoring and Optimization: Implement monitoring tools and strategies to optimize the performance of data systems.
  
   

Qualifications:

• Education: Bachelor’s degree in Computer Science, Engineering, or a related field.
• Experience: Minimum of 5 years in data engineering roles with experience in AWS services. Proven track record in building scalable data architectures.
• Technical Skills: Proficiency in AWS tools (e.g., S3, RDS, Redshift, Glue), data processing frameworks (e.g., Apache Spark, Hadoop), and programming languages (e.g., Python, SQL).
• Analytical Skills: Strong problem-solving abilities and a data-driven mindset. Experience with performance tuning and data optimization.
• Communication Skills: Excellent verbal and written communication skills. Ability to collaborate effectively with cross-functional teams.
• Attention to Detail: High attention to detail and a commitment to delivering high-quality solutions.

Additional requirements

• Certifications: AWS Certified Data Analytics – Specialty, AWS Certified Solutions Architect, or similar certifications.
• Domain Knowledge: Experience in the automotive industry or digital marketing sector.

Additional Skills: Familiarity with machine learning models and integration with customer-facing applications.