During my time as Head of Professional Services for a private Genomics based company I spearheaded an initiative to utilise an open source offline LLM for analysing our Jira, Confluence and Salesforce docs for quick retrieval of process and technical information.

The purpose was twofold,

a) To create a common ‘search’ tool in order to locate a source of truth as to what was configured and where, and

b) To be able to generate process documents very quickly in whole or in part through the use of generative AI.

As these were sensitive company documents, use of a service like ChatGPT was restricted, which is why we opted to trial PrivateGPT with Llama-2-7b amongst other models.

We found RAG to be less than perfect, but it did effectively allow us to search out the right documents. Text generation was better in that we managed to produce good content as an initial template for a process guides, as well as feeding a full process document to generate a RASCI chart. We ran the pilot service on AWS EC2 infrastruture.

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As Head of Professional Services I developed and introduced a new billable service for customers which allowed them to receive monthly or quartery exports of analysed sequence data for their use in predicting trends.

This involved the export of large sequenced data in the form of VCF SNV files. I managed the project team which included a Project Manager, Bioinformatics Consultant, DBA and DevOps in order to ensure the first customer was properly onboarded and that the customer would receive notifications when the data export was ready.

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As Head of Professional Services I took over responsibility for a number of software integrations written by a bioinformatics consultant who had previously left the company. One of these integrations was supplied to a parnter organisation and had been reported to have an undetected design flaw which raised a ‘highest severity’ ticket. No-one in my team was familiar with the code, so I had to reach out and coordinate with DevOps and Engineering for assistance.

Through bargaining and persistance I secured some time of one of the lead bioinformaticians to take a look at the code, review the clients requirements and make the changes. This was the easiest part – I recognised the issue with the code myself, but as I wouldn’t understand the genomics interpretation part, I did not want to make edits myself. The second part of the issue was with clinical decisions that had already been made with the flawed code. There was little that I could do here, but it was down to me to make sure that the right resources were aware and assigned to figure out which decisions had been impacted to report back to the client.

The code fix was done within SLAs, finding the impacted clinical decisions took longer. My final action was to ensure that the application was correctly documented for future support and ensure that the client sign off on the new implementation of the code (to ensure that there is record of agreement that it now worked as expected – which was missing before).

I was also engaged with this partner through organising a resource to work on custom reporting, using a combination of python and flask. I acted as liaison and project manager with the customer ensuring that the code was developed to specification and that milestones for delivery, test and sign off were met.

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I was responsible for the improving the managed service architecture of a multi-year service contract already in-flight. There had been significant issues raised over the quality of the service up until my engagemement.

The main complaints were:

• Support resource not seen to be solving any reported issues
• Missing roadmap meetings
• Not feeling the value

An action plan and strategy was put in place, for me to conduct quarterly service reviews where I would present the latest features of the products and recommend strategy for upgrade and utilisation of these features, including any enhancements we could provide to the service.

The support resource issue was identified as being a follow on outcome of the customer not willing to log tickets and instead engaging the named resource directly. In this way the resource was being treated as a contractor and being asked to work on various unspecified tasks and issues. In discussing the issue with the client, I suggested they could either continue with no SLAs and agree to the support resource under 1-day per week effort, or that in order for us to track performance and ensure requests were deailt with, they would need to engage with the service and log tickets.

However, as many of the requests would have been out of the scope of the service and meant engagement with professional services, they did not want to implement this change. They prefered to carry on under the existing arrangement, without further complaint.

During this time I was also able to implement health checks for them and identify a number of security vulnerabilites which were esclated to their CISO. One was the identification of plaintext username/password strings in running processes, and the other was production level software running under a non-service account credential.

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I was contracted to help win a bid for providing a managed service worth $200k to a large US-based vehicle manufacturer. They were intially discussing a multi-year deal for plant inventory discovery, however it was quickly realised by the client that it would make sense to turn this into a managed service.

The service included upgrade of current Discovery solution with right-sizing the architecture, installation of Remedy with CMDB and support services. The scope of Discovery was to scan the plant networks – the challenge being that these were on profinet and were not only sensitive equipment but scanning was only permitted under very strict windows.

We managed to complete the implementation of the solution upgrade and installation, with the implementation of the full managed service coming later due to delays on the client end. As part of value add of the service, the customer was also provided with a custom solution I developed in python that worked with the Discovery API to be able to load IP ranges with updated location information and automatically update the scan data and schedules.

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I was in charge of the architecture for the deployment £200k worth of solutions and a managed service for a large German consulting firm that wanted to implement a new Asset & Configuration Management function using BMC’s toolset.

Once the deployment was completed and the customer onboarded, I acted as an 3rd line escalation point issues logged through the managed service. In particular I got involved with issues with Data Quality and modelling their network environments. As part of the service they were also gauranteed regular health checks – which we provided in the form of a unique set of analytics written in Python which were exported to Power BI for presenting insights back to the customer, such as:

• Root user logins
• Vulernable open ports
• Recommendations for search and query optimisation
• Compliance issues
• Data quality issues

This unique service was provided only by the company I was working for at the time where I developed it.

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I was hired as a Delivery Manager and Enterprise Architect for the global rollout of Discovery and CMDB for an international Managment Consulting company. This was a 2 year programme directed at North America and European regions worth €2m.

In the first year I identified and implemented €90k worth of cost savings to the programme by automating level 1 support so that the resources were no longer required. I led a team of 8 offshore engineers in India and Poland and was responsible for their training and managing their progress on the the deployment to individual accounts.

I reported to the Programme Manager and was responsible for not only the software architecture but the security design needed to obtain global CISO sign off and allow the programme to proceed when it hit a major hurdle and was blocked by security compliance. One of the many hurdles was implementing RBAC into the solution which had not been designed for full RBAC control.

I worked with one of my lead engineers to find and document all the group permissions available in the tool, then employed a hack to prevent certain pages from loading without the right permissions. This satisfied the requirements of Global CISO. During the process we even discovered a vulnerability that allowed access without permissions, which was reported back to the vendor. The vendor was so impressed that they asked if they could see our documentation.

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I have developed comprehensive health checks for BMC Discovery, Kubernetes, NFS and PostgreSQL. I have also developed exception reporting on data pipelines for data quality assessment. The health checks I have developed have saved customers in the following areas:

• Identified security vulnerabilities around plaintext usernames and passwords storage
• Identified issues around NFS performance
• Identified opportunities for license reclaimation
• Identified usage patterns for insecure practices (i.e. logging in as root user)
• Identified various misconfigurations in non-alignment with best practices

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